Civilingenjör i datateknik - Lediga jobb

Vill du arbeta programmeringstungt med stora datamängder, utveckla nya modeller och påverka på riktigt? Just nu gör Swedbank en stor strategisk satsning och gör ett ordentligt omtag av deras modeller för lönsamhetsstyrning. Till detta affärskritiska arbete söker vi nu en Data Scientists som vill vara med och forma framtidens ramverk. Du erbjuds en brant lärandekurva i ett stöttande, öppet och socialt team där din potential och din nyfikenhet värderas allra högst.

Om tjänsten

Du kommer att tillhöra ett tight och kompetent team bestående av fyra Data Scientists samt teamchefen Elin. Teamet arbetar tekniskt och analytiskt i SAS, SQL och Python, men de är långt ifrån det stelbenta analytikerteam du kanske föreställer dig. De är ett öppet, socialt och ganska extrovert gäng som har högt i tak, stöttar varandra i vardagen och gillar att hitta på roliga saker tillsammans.

Som person är du samarbetsinriktad, lösningsorienterad och transparent. Du bidrar positivt till stämningen i teamet, kommunicerar tydligt med olika intressenter och känner dig bekväm med att utmana antaganden när det behövs. Du trivs med att arbeta med komplexa frågeställningar, tar ägarskap för dina leveranser och har en stark känsla för kvalitet.

Du erbjuds

• En roll med stor påverkan på bankens framtida ramverk och metoder. I det stöttande teamet får du goda möjligheter att utvecklas tekniskt inom Python och SQL samtidigt som du bygger en djup förståelse för bankaffären.
• En visstidsanställning hos Academic Work där goda möjligheter till överrekrytering finns efter 6-12 månader. Vi erbjuder även fast månadslön.

Arbetsuppgifter

• Använda din analytiska förmåga till att hantera komplexa utmaningar och göra skillnad inom det affärskritiska området riskjusterad finansiell styrning.
• Bidra till utvecklingen av nya modeller och metoder för kapitalallokering och riskjusterad lönsamhetsstyrning inom den svenska företagsaffären.
• Arbeta med stora datamängder för att genomföra kvantitativa analyser och ta fram insikter för att förbättra modellprestanda.
• Tillämpa datadriven analys för att identifiera möjligheter till ökad kapitaleffektivitet och förbättringar av kapitalberäkningar.

Vi söker dig som

• Akademisk examen inom matematik, statistik eller industriell ekonomi.
• Goda kunskaper i SAS/SQL, R eller Python.
• God förmåga att utföra kvantitativ analys och datamodellering.
• Bekväm med att arbeta med stora och komplexa datamängder.
• Flytande kunskaper i svenska och engelska i både tal och skrift.

Det är meriterande om du har

• Erfarenhet från analytiska roller inom kreditrisk, modellering (IRB/IFRS 9), ICAAP, stresstester eller kapitalhantering.
• Tidigare erfarenhet av finansmatematik eller affärsstyrning inom bank.

För att lyckas i rollen har du följande personliga egenskaper:

• Hjälpsam
• Målmedveten
• Social
• Ansvarstagande
• Energisk
• Intellektuellt nyfiken

Vår rekryteringsprocess

Denna rekryteringsprocess hanteras av Academic Work och vår kunds önskemål är att alla frågor rörande tjänsten skickas till Academic Work.

Vi tillämpar löpande urval och kommer plocka ner annonsen när tillräckligt många kandidater har nått slutskedet i rekryteringsprocessen. Vid ansökan efterfrågas ett CV. Personligt brev använder vi inte som urvalsmetod och behöver därför inte bifogas. Rekryteringsprocessen innehåller två urvalstest: ett personlighetstest och ett test i kognitiv förmåga. Testerna är ett verktyg för att kunna hitta den kandidat med högst potential för tjänsten samt främja jämlikhet, mångfald och en rättvis rekryteringsprocess.

Data and AI are becoming increasingly important in how we build better products, support smarter decisions, and create value across Schibsted Media. We are looking for a Senior Data Engineer who wants to help shape reliable, scalable, and well-governed data products used across our media brands.

In this role, you will work in the intersection of data engineering, analytics engineering, and platform thinking. You will help us build trusted data models, improve how we work with data pipelines, and guide technical direction for a team working closely with stakeholders across Finance, HR, Product, Subscription, and other data & AI teams.

You will join the Data & AI organization in the Data Product Engineering team, where we build data capabilities that help teams across Schibsted Media make better decisions, create trusted data products, and enable future AI use cases.

We are looking for someone who can be both hands-on and guiding. You do not need to be the loudest person in the room, but you should be able to create clarity, make pragmatic technical decisions, and help other engineers grow.

You will play a key role in shaping how we build data as a product. This includes creating data models that are reliable, well-documented, and designed for real use cases, not just pipelines that move data.

As a senior member of the team, you will also help create good engineering practices, mentor more junior engineers, and collaborate closely with adjacent teams working on data platforms and shared tooling.

As part of a newly formed team of Data / Analytics Engineers, you'll have the opportunity to influence how we work, shape our engineering culture, and make a real impact from day one. We're now looking for 2–3 more engineers to join us on the journey.

• Collaborate closely with stakeholders to understand needs, clarify tradeoffs, and deliver pragmatic solutions

• Design, build, and maintain robust data pipelines using technologies such as Snowflake, dbt, and Airflow

• Develop scalable and maintainable data models that support analytics, reporting, and AI use cases

• Help define best practices for data modeling, transformation, testing, documentation, and governance

• Mentor junior engineers and support the team in making good technical decisions

• Work with adjacent Data & AI teams to align on platform capabilities, standards, and shared ways of working

• Improve reliability, performance, cost-efficiency, and scalability of our data solutions

• Contribute to a culture of ownership, learning, and continuous improvement

• Solid experience as a Data Engineer or similar role

• Strong SQL skills and good understanding of data warehousing concepts

• Experience with data modeling and building data products for analytics or reporting

• Experience with modern data transformation and orchestration tools (e.g. dbt, Airflow or similar)

• Ability to take ownership and make pragmatic technical decisions in ambiguous and evolving environments

• Strong communication skills and ability to work with both technical and non-technical stakeholders. English is our main working language.

• Collaborative mindset and ability to work well across teams

• Experience with Python or scripting for data engineering workflows

• Experience with CI/CD, GitOps, and version control best practices

• Experience with cloud platforms such as AWS, GCP, or Azure

• Experience with data quality, observability, governance, or access control

• Experience as a senior engineer in a cross-functional environment

• High ownership and influence in shaping technical direction and ways of working

• Opportunity to shape trusted data products with real impact across Schibsted Media

• Flexible working hours and hybrid work options with strong trust and autonomy

• International environment with offices in Oslo, Stockholm, and Krakow

• Strong learning culture with learning budget and active engineering & AI communities

• Access to Schibsted’s media products, including premium news and podcasts

You enjoy turning messy problems into clear, maintainable solutions. You care about technical quality, but you also understand that good engineering is about tradeoffs, communication, and delivering value.

You are comfortable working in an environment where not everything is fully defined yet. You help create structure, bring others along, and make the team better through your technical judgment and collaboration.

When you apply, we'd love to get to know the real you. We value authentic applications and are much more interested in your own thoughts, experiences, and motivations than polished AI-generated content.

If you want to help build trusted data products that enable better decisions and future AI capabilities across Schibsted Media, we would love to hear from you.

Data and AI are becoming increasingly important in how we build better products, support smarter decisions, and create value across Schibsted Media. We are looking for a Data Engineer who wants to help build reliable, scalable, and well-governed data products used across our media brands.

In this role, you will work at the intersection of data engineering, analytics engineering, and platform thinking. You will help us build trusted data models, improve data pipelines, and collaborate closely with stakeholders across Finance, HR, Product, Subscription, and other Data & AI teams.

You will join the Data & AI organization in the Data Product Engineering team, where we build data capabilities that help teams across Schibsted Media make better decisions, create trusted data products, and enable future AI use cases.

We are looking for someone who enjoys building solid data solutions and working closely with others to turn business needs into useful, maintainable data products.

You do not need to have all the answers, but you should be curious, structured, and willing to take ownership of your work. You will contribute to how we build data as a product, including creating data models that are reliable, well-documented, and designed for real use cases, not just pipelines that move data.

As part of a newly formed team of Data / Analytics Engineers, you will work with fellow data engineers, collaborate with adjacent teams, and help improve our engineering practices over time. You'll have the opportunity to influence how we work, shape our engineering culture, and make a real impact from day one. We're now looking for 2–3 more engineers to join us on the journey.

• Collaborate with stakeholders to understand needs, clarify requirements, and deliver pragmatic data solutions

• Design, build, and maintain data pipelines using technologies such as Snowflake, dbt, and Airflow

• Develop maintainable data models that support analytics, reporting, and AI use cases

• Contribute to good practices for data modeling, transformation, testing, documentation, and governance

• Work with other Data & AI teams to align on platform capabilities, standards, and shared ways of working

• Help improve reliability, performance, cost-efficiency, and scalability of our data solutions

• Participate in code reviews, technical discussions, and continuous improvement of our ways of working

• Contribute to a culture of ownership, learning, and collaboration

• 3+ years experience as a Data Engineer, Analytics Engineer, or similar role

• Strong SQL skills and good understanding of data warehousing concepts

• Experience building data pipelines or data models for analytics, reporting, or product use cases

• Experience with modern data transformation or orchestration tools, such as dbt, Airflow, or similar

• Ability to take ownership of tasks and deliver maintainable solutions

• Good communication skills and ability to work with both technical and non-technical stakeholders. English is our main working language.

• Collaborative mindset and willingness to learn from and contribute to the team

• Experience with Python or scripting for data engineering workflows

• Experience with Snowflake, dbt, Airflow, or similar tools

• Experience with CI/CD, version control, and engineering best practices

• Experience with cloud platforms such as AWS, GCP, or Azure

• Interest in data quality, observability, governance, or access control

• Experience working in a cross-functional or product-oriented environment

• Opportunity to build trusted data products with real impact across Schibsted Media

• A role with ownership, learning opportunities, and support from experienced colleagues

• Flexible working hours and hybrid work options with strong trust and autonomy

• International environment with offices in Oslo, Stockholm, and Krakow

• Strong learning culture with learning budget and active engineering & AI communities

• Access to Schibsted’s media products, including premium news and podcasts

You enjoy turning messy problems into clear, maintainable solutions. You care about technical quality, but you also understand that good engineering is about tradeoffs, communication, and delivering value.

You are comfortable asking questions, learning from others, and taking responsibility for your work. You like collaborating with stakeholders and teammates, and you want to grow as an engineer while contributing to data products that are useful, trusted, and impactful.

When you apply, we'd love to get to know the real you. We value authentic applications and are much more interested in your own thoughts, experiences, and motivations than polished AI-generated content.

If you want to help build trusted data products that enable better decisions and future AI capabilities across Schibsted Media, we would love to hear from you.

Data and AI are becoming increasingly important in how we build better products, support smarter decisions, and create value across Schibsted Media. We are looking for a Data Engineer who wants to help build reliable, scalable, and well-governed data products used across our media brands.

In this role, you will work at the intersection of data engineering, analytics engineering, and platform thinking. You will help us build trusted data models, improve data pipelines, and collaborate closely with stakeholders across Finance, HR, Product, Subscription, and other Data & AI teams.

You will join the Data & AI organization in the Data Product Engineering team, where we build data capabilities that help teams across Schibsted Media make better decisions, create trusted data products, and enable future AI use cases.

We are looking for someone who enjoys building solid data solutions and working closely with others to turn business needs into useful, maintainable data products.

You do not need to have all the answers, but you should be curious, structured, and willing to take ownership of your work. You will contribute to how we build data as a product, including creating data models that are reliable, well-documented, and designed for real use cases, not just pipelines that move data.

As part of a newly formed team of Data / Analytics Engineers, you will work with fellow data engineers, collaborate with adjacent teams, and help improve our engineering practices over time. You'll have the opportunity to influence how we work, shape our engineering culture, and make a real impact from day one. We're now looking for 2–3 more engineers to join us on the journey.

• Collaborate with stakeholders to understand needs, clarify requirements, and deliver pragmatic data solutions

• Design, build, and maintain data pipelines using technologies such as Snowflake, dbt, and Airflow

• Develop maintainable data models that support analytics, reporting, and AI use cases

• Contribute to good practices for data modeling, transformation, testing, documentation, and governance

• Work with other Data & AI teams to align on platform capabilities, standards, and shared ways of working

• Help improve reliability, performance, cost-efficiency, and scalability of our data solutions

• Participate in code reviews, technical discussions, and continuous improvement of our ways of working

• Contribute to a culture of ownership, learning, and collaboration

• 3+ years experience as a Data Engineer, Analytics Engineer, or similar role

• Strong SQL skills and good understanding of data warehousing concepts

• Experience building data pipelines or data models for analytics, reporting, or product use cases

• Experience with modern data transformation or orchestration tools, such as dbt, Airflow, or similar

• Ability to take ownership of tasks and deliver maintainable solutions

• Good communication skills and ability to work with both technical and non-technical stakeholders. English is our main working language.

• Collaborative mindset and willingness to learn from and contribute to the team

• Experience with Python or scripting for data engineering workflows

• Experience with Snowflake, dbt, Airflow, or similar tools

• Experience with CI/CD, version control, and engineering best practices

• Experience with cloud platforms such as AWS, GCP, or Azure

• Interest in data quality, observability, governance, or access control

• Experience working in a cross-functional or product-oriented environment

• Opportunity to build trusted data products with real impact across Schibsted Media

• A role with ownership, learning opportunities, and support from experienced colleagues

• Flexible working hours and hybrid work options with strong trust and autonomy

• International environment with offices in Oslo, Stockholm, and Krakow

• Strong learning culture with learning budget and active engineering & AI communities

• Access to Schibsted’s media products, including premium news and podcasts

You enjoy turning messy problems into clear, maintainable solutions. You care about technical quality, but you also understand that good engineering is about tradeoffs, communication, and delivering value.

You are comfortable asking questions, learning from others, and taking responsibility for your work. You like collaborating with stakeholders and teammates, and you want to grow as an engineer while contributing to data products that are useful, trusted, and impactful.

When you apply, we'd love to get to know the real you. We value authentic applications and are much more interested in your own thoughts, experiences, and motivations than polished AI-generated content.

If you want to help build trusted data products that enable better decisions and future AI capabilities across Schibsted Media, we would love to hear from you.

Data and AI are becoming increasingly important in how we build better products, support smarter decisions, and create value across Schibsted Media. We are looking for a Senior Data Engineer who wants to help shape reliable, scalable, and well-governed data products used across our media brands.

In this role, you will work in the intersection of data engineering, analytics engineering, and platform thinking. You will help us build trusted data models, improve how we work with data pipelines, and guide technical direction for a team working closely with stakeholders across Finance, HR, Product, Subscription, and other data & AI teams.

You will join the Data & AI organization in the Data Product Engineering team, where we build data capabilities that help teams across Schibsted Media make better decisions, create trusted data products, and enable future AI use cases.

We are looking for someone who can be both hands-on and guiding. You do not need to be the loudest person in the room, but you should be able to create clarity, make pragmatic technical decisions, and help other engineers grow.

You will play a key role in shaping how we build data as a product. This includes creating data models that are reliable, well-documented, and designed for real use cases, not just pipelines that move data.

As a senior member of the team, you will also help create good engineering practices, mentor more junior engineers, and collaborate closely with adjacent teams working on data platforms and shared tooling.

As part of a newly formed team of Data / Analytics Engineers, you'll have the opportunity to influence how we work, shape our engineering culture, and make a real impact from day one. We're now looking for 2–3 more engineers to join us on the journey.

• Collaborate closely with stakeholders to understand needs, clarify tradeoffs, and deliver pragmatic solutions

• Design, build, and maintain robust data pipelines using technologies such as Snowflake, dbt, and Airflow

• Develop scalable and maintainable data models that support analytics, reporting, and AI use cases

• Help define best practices for data modeling, transformation, testing, documentation, and governance

• Mentor junior engineers and support the team in making good technical decisions

• Work with adjacent Data & AI teams to align on platform capabilities, standards, and shared ways of working

• Improve reliability, performance, cost-efficiency, and scalability of our data solutions

• Contribute to a culture of ownership, learning, and continuous improvement

• Solid experience as a Data Engineer or similar role

• Strong SQL skills and good understanding of data warehousing concepts

• Experience with data modeling and building data products for analytics or reporting

• Experience with modern data transformation and orchestration tools (e.g. dbt, Airflow or similar)

• Ability to take ownership and make pragmatic technical decisions in ambiguous and evolving environments

• Strong communication skills and ability to work with both technical and non-technical stakeholders. English is our main working language.

• Collaborative mindset and ability to work well across teams

• Experience with Python or scripting for data engineering workflows

• Experience with CI/CD, GitOps, and version control best practices

• Experience with cloud platforms such as AWS, GCP, or Azure

• Experience with data quality, observability, governance, or access control

• Experience as a senior engineer in a cross-functional environment

• High ownership and influence in shaping technical direction and ways of working

• Opportunity to shape trusted data products with real impact across Schibsted Media

• Flexible working hours and hybrid work options with strong trust and autonomy

• International environment with offices in Oslo, Stockholm, and Krakow

• Strong learning culture with learning budget and active engineering & AI communities

• Access to Schibsted’s media products, including premium news and podcasts

You enjoy turning messy problems into clear, maintainable solutions. You care about technical quality, but you also understand that good engineering is about tradeoffs, communication, and delivering value.

You are comfortable working in an environment where not everything is fully defined yet. You help create structure, bring others along, and make the team better through your technical judgment and collaboration.

When you apply, we'd love to get to know the real you. We value authentic applications and are much more interested in your own thoughts, experiences, and motivations than polished AI-generated content.

If you want to help build trusted data products that enable better decisions and future AI capabilities across Schibsted Media, we would love to hear from you.

Data and AI are becoming increasingly important in how we build better products, support smarter decisions, and create value across Schibsted Media. We are looking for a Data Engineer who wants to help build reliable, scalable, and well-governed data products used across our media brands.

In this role, you will work at the intersection of data engineering, analytics engineering, and platform thinking. You will help us build trusted data models, improve data pipelines, and collaborate closely with stakeholders across Finance, HR, Product, Subscription, and other Data & AI teams.

You will join the Data & AI organization in the Data Product Engineering team, where we build data capabilities that help teams across Schibsted Media make better decisions, create trusted data products, and enable future AI use cases.

We are looking for someone who enjoys building solid data solutions and working closely with others to turn business needs into useful, maintainable data products.

You do not need to have all the answers, but you should be curious, structured, and willing to take ownership of your work. You will contribute to how we build data as a product, including creating data models that are reliable, well-documented, and designed for real use cases, not just pipelines that move data.

As part of a newly formed team of Data / Analytics Engineers, you will work with fellow data engineers, collaborate with adjacent teams, and help improve our engineering practices over time. You'll have the opportunity to influence how we work, shape our engineering culture, and make a real impact from day one. We're now looking for 2–3 more engineers to join us on the journey.

• Collaborate with stakeholders to understand needs, clarify requirements, and deliver pragmatic data solutions

• Design, build, and maintain data pipelines using technologies such as Snowflake, dbt, and Airflow

• Develop maintainable data models that support analytics, reporting, and AI use cases

• Contribute to good practices for data modeling, transformation, testing, documentation, and governance

• Work with other Data & AI teams to align on platform capabilities, standards, and shared ways of working

• Help improve reliability, performance, cost-efficiency, and scalability of our data solutions

• Participate in code reviews, technical discussions, and continuous improvement of our ways of working

• Contribute to a culture of ownership, learning, and collaboration

• 3+ years experience as a Data Engineer, Analytics Engineer, or similar role

• Strong SQL skills and good understanding of data warehousing concepts

• Experience building data pipelines or data models for analytics, reporting, or product use cases

• Experience with modern data transformation or orchestration tools, such as dbt, Airflow, or similar

• Ability to take ownership of tasks and deliver maintainable solutions

• Good communication skills and ability to work with both technical and non-technical stakeholders. English is our main working language.

• Collaborative mindset and willingness to learn from and contribute to the team

• Experience with Python or scripting for data engineering workflows

• Experience with Snowflake, dbt, Airflow, or similar tools

• Experience with CI/CD, version control, and engineering best practices

• Experience with cloud platforms such as AWS, GCP, or Azure

• Interest in data quality, observability, governance, or access control

• Experience working in a cross-functional or product-oriented environment

• Opportunity to build trusted data products with real impact across Schibsted Media

• A role with ownership, learning opportunities, and support from experienced colleagues

• Flexible working hours and hybrid work options with strong trust and autonomy

• International environment with offices in Oslo, Stockholm, and Krakow

• Strong learning culture with learning budget and active engineering & AI communities

• Access to Schibsted’s media products, including premium news and podcasts

You enjoy turning messy problems into clear, maintainable solutions. You care about technical quality, but you also understand that good engineering is about tradeoffs, communication, and delivering value.

You are comfortable asking questions, learning from others, and taking responsibility for your work. You like collaborating with stakeholders and teammates, and you want to grow as an engineer while contributing to data products that are useful, trusted, and impactful.

When you apply, we'd love to get to know the real you. We value authentic applications and are much more interested in your own thoughts, experiences, and motivations than polished AI-generated content.

If you want to help build trusted data products that enable better decisions and future AI capabilities across Schibsted Media, we would love to hear from you.

Data and AI are becoming increasingly important in how we build better products, support smarter decisions, and create value across Schibsted Media. We are looking for a Senior Data Engineer who wants to help shape reliable, scalable, and well-governed data products used across our media brands.

In this role, you will work in the intersection of data engineering, analytics engineering, and platform thinking. You will help us build trusted data models, improve how we work with data pipelines, and guide technical direction for a team working closely with stakeholders across Finance, HR, Product, Subscription, and other data & AI teams.

You will join the Data & AI organization in the Data Product Engineering team, where we build data capabilities that help teams across Schibsted Media make better decisions, create trusted data products, and enable future AI use cases.

We are looking for someone who can be both hands-on and guiding. You do not need to be the loudest person in the room, but you should be able to create clarity, make pragmatic technical decisions, and help other engineers grow.

You will play a key role in shaping how we build data as a product. This includes creating data models that are reliable, well-documented, and designed for real use cases, not just pipelines that move data.

As a senior member of the team, you will also help create good engineering practices, mentor more junior engineers, and collaborate closely with adjacent teams working on data platforms and shared tooling.

As part of a newly formed team of Data / Analytics Engineers, you'll have the opportunity to influence how we work, shape our engineering culture, and make a real impact from day one. We're now looking for 2–3 more engineers to join us on the journey.

• Collaborate closely with stakeholders to understand needs, clarify tradeoffs, and deliver pragmatic solutions

• Design, build, and maintain robust data pipelines using technologies such as Snowflake, dbt, and Airflow

• Develop scalable and maintainable data models that support analytics, reporting, and AI use cases

• Help define best practices for data modeling, transformation, testing, documentation, and governance

• Mentor junior engineers and support the team in making good technical decisions

• Work with adjacent Data & AI teams to align on platform capabilities, standards, and shared ways of working

• Improve reliability, performance, cost-efficiency, and scalability of our data solutions

• Contribute to a culture of ownership, learning, and continuous improvement

• Solid experience as a Data Engineer or similar role

• Strong SQL skills and good understanding of data warehousing concepts

• Experience with data modeling and building data products for analytics or reporting

• Experience with modern data transformation and orchestration tools (e.g. dbt, Airflow or similar)

• Ability to take ownership and make pragmatic technical decisions in ambiguous and evolving environments

• Strong communication skills and ability to work with both technical and non-technical stakeholders. English is our main working language.

• Collaborative mindset and ability to work well across teams

• Experience with Python or scripting for data engineering workflows

• Experience with CI/CD, GitOps, and version control best practices

• Experience with cloud platforms such as AWS, GCP, or Azure

• Experience with data quality, observability, governance, or access control

• Experience as a senior engineer in a cross-functional environment

• High ownership and influence in shaping technical direction and ways of working

• Opportunity to shape trusted data products with real impact across Schibsted Media

• Flexible working hours and hybrid work options with strong trust and autonomy

• International environment with offices in Oslo, Stockholm, and Krakow

• Strong learning culture with learning budget and active engineering & AI communities

• Access to Schibsted’s media products, including premium news and podcasts

You enjoy turning messy problems into clear, maintainable solutions. You care about technical quality, but you also understand that good engineering is about tradeoffs, communication, and delivering value.

You are comfortable working in an environment where not everything is fully defined yet. You help create structure, bring others along, and make the team better through your technical judgment and collaboration.

When you apply, we'd love to get to know the real you. We value authentic applications and are much more interested in your own thoughts, experiences, and motivations than polished AI-generated content.

If you want to help build trusted data products that enable better decisions and future AI capabilities across Schibsted Media, we would love to hear from you.

Data and AI are becoming increasingly important in how we build better products, support smarter decisions, and create value across Schibsted Media. We are looking for a Data Engineer who wants to help build reliable, scalable, and well-governed data products used across our media brands.

In this role, you will work at the intersection of data engineering, analytics engineering, and platform thinking. You will help us build trusted data models, improve data pipelines, and collaborate closely with stakeholders across Finance, HR, Product, Subscription, and other Data & AI teams.

You will join the Data & AI organization in the Data Product Engineering team, where we build data capabilities that help teams across Schibsted Media make better decisions, create trusted data products, and enable future AI use cases.

We are looking for someone who enjoys building solid data solutions and working closely with others to turn business needs into useful, maintainable data products.

You do not need to have all the answers, but you should be curious, structured, and willing to take ownership of your work. You will contribute to how we build data as a product, including creating data models that are reliable, well-documented, and designed for real use cases, not just pipelines that move data.

As part of a newly formed team of Data / Analytics Engineers, you will work with fellow data engineers, collaborate with adjacent teams, and help improve our engineering practices over time. You'll have the opportunity to influence how we work, shape our engineering culture, and make a real impact from day one. We're now looking for 2–3 more engineers to join us on the journey.

• Collaborate with stakeholders to understand needs, clarify requirements, and deliver pragmatic data solutions

• Design, build, and maintain data pipelines using technologies such as Snowflake, dbt, and Airflow

• Develop maintainable data models that support analytics, reporting, and AI use cases

• Contribute to good practices for data modeling, transformation, testing, documentation, and governance

• Work with other Data & AI teams to align on platform capabilities, standards, and shared ways of working

• Help improve reliability, performance, cost-efficiency, and scalability of our data solutions

• Participate in code reviews, technical discussions, and continuous improvement of our ways of working

• Contribute to a culture of ownership, learning, and collaboration

• 3+ years experience as a Data Engineer, Analytics Engineer, or similar role

• Strong SQL skills and good understanding of data warehousing concepts

• Experience building data pipelines or data models for analytics, reporting, or product use cases

• Experience with modern data transformation or orchestration tools, such as dbt, Airflow, or similar

• Ability to take ownership of tasks and deliver maintainable solutions

• Good communication skills and ability to work with both technical and non-technical stakeholders. English is our main working language.

• Collaborative mindset and willingness to learn from and contribute to the team

• Experience with Python or scripting for data engineering workflows

• Experience with Snowflake, dbt, Airflow, or similar tools

• Experience with CI/CD, version control, and engineering best practices

• Experience with cloud platforms such as AWS, GCP, or Azure

• Interest in data quality, observability, governance, or access control

• Experience working in a cross-functional or product-oriented environment

• Opportunity to build trusted data products with real impact across Schibsted Media

• A role with ownership, learning opportunities, and support from experienced colleagues

• Flexible working hours and hybrid work options with strong trust and autonomy

• International environment with offices in Oslo, Stockholm, and Krakow

• Strong learning culture with learning budget and active engineering & AI communities

• Access to Schibsted’s media products, including premium news and podcasts

You enjoy turning messy problems into clear, maintainable solutions. You care about technical quality, but you also understand that good engineering is about tradeoffs, communication, and delivering value.

You are comfortable asking questions, learning from others, and taking responsibility for your work. You like collaborating with stakeholders and teammates, and you want to grow as an engineer while contributing to data products that are useful, trusted, and impactful.

When you apply, we'd love to get to know the real you. We value authentic applications and are much more interested in your own thoughts, experiences, and motivations than polished AI-generated content.

If you want to help build trusted data products that enable better decisions and future AI capabilities across Schibsted Media, we would love to hear from you.

Data and AI are becoming increasingly important in how we build better products, support smarter decisions, and create value across Schibsted Media. We are looking for a Senior Data Engineer who wants to help shape reliable, scalable, and well-governed data products used across our media brands.

In this role, you will work in the intersection of data engineering, analytics engineering, and platform thinking. You will help us build trusted data models, improve how we work with data pipelines, and guide technical direction for a team working closely with stakeholders across Finance, HR, Product, Subscription, and other data & AI teams.

You will join the Data & AI organization in the Data Product Engineering team, where we build data capabilities that help teams across Schibsted Media make better decisions, create trusted data products, and enable future AI use cases.

We are looking for someone who can be both hands-on and guiding. You do not need to be the loudest person in the room, but you should be able to create clarity, make pragmatic technical decisions, and help other engineers grow.

You will play a key role in shaping how we build data as a product. This includes creating data models that are reliable, well-documented, and designed for real use cases, not just pipelines that move data.

As a senior member of the team, you will also help create good engineering practices, mentor more junior engineers, and collaborate closely with adjacent teams working on data platforms and shared tooling.

As part of a newly formed team of Data / Analytics Engineers, you'll have the opportunity to influence how we work, shape our engineering culture, and make a real impact from day one. We're now looking for 2–3 more engineers to join us on the journey.

• Collaborate closely with stakeholders to understand needs, clarify tradeoffs, and deliver pragmatic solutions

• Design, build, and maintain robust data pipelines using technologies such as Snowflake, dbt, and Airflow

• Develop scalable and maintainable data models that support analytics, reporting, and AI use cases

• Help define best practices for data modeling, transformation, testing, documentation, and governance

• Mentor junior engineers and support the team in making good technical decisions

• Work with adjacent Data & AI teams to align on platform capabilities, standards, and shared ways of working

• Improve reliability, performance, cost-efficiency, and scalability of our data solutions

• Contribute to a culture of ownership, learning, and continuous improvement

• Solid experience as a Data Engineer or similar role

• Strong SQL skills and good understanding of data warehousing concepts

• Experience with data modeling and building data products for analytics or reporting

• Experience with modern data transformation and orchestration tools (e.g. dbt, Airflow or similar)

• Ability to take ownership and make pragmatic technical decisions in ambiguous and evolving environments

• Strong communication skills and ability to work with both technical and non-technical stakeholders. English is our main working language.

• Collaborative mindset and ability to work well across teams

• Experience with Python or scripting for data engineering workflows

• Experience with CI/CD, GitOps, and version control best practices

• Experience with cloud platforms such as AWS, GCP, or Azure

• Experience with data quality, observability, governance, or access control

• Experience as a senior engineer in a cross-functional environment

• High ownership and influence in shaping technical direction and ways of working

• Opportunity to shape trusted data products with real impact across Schibsted Media

• Flexible working hours and hybrid work options with strong trust and autonomy

• International environment with offices in Oslo, Stockholm, and Krakow

• Strong learning culture with learning budget and active engineering & AI communities

• Access to Schibsted’s media products, including premium news and podcasts

You enjoy turning messy problems into clear, maintainable solutions. You care about technical quality, but you also understand that good engineering is about tradeoffs, communication, and delivering value.

You are comfortable working in an environment where not everything is fully defined yet. You help create structure, bring others along, and make the team better through your technical judgment and collaboration.

When you apply, we'd love to get to know the real you. We value authentic applications and are much more interested in your own thoughts, experiences, and motivations than polished AI-generated content.

If you want to help build trusted data products that enable better decisions and future AI capabilities across Schibsted Media, we would love to hear from you.

Vill du arbeta programmeringstungt med stora datamängder, utveckla nya modeller och påverka på riktigt? Just nu gör Swedbank en stor strategisk satsning och gör ett ordentligt omtag av deras modeller för lönsamhetsstyrning. Till detta affärskritiska arbete söker vi nu en Data Scientists som vill vara med och forma framtidens ramverk. Du erbjuds en brant lärandekurva i ett stöttande, öppet och socialt team där din potential och din nyfikenhet värderas allra högst.

Om tjänsten

Du kommer att tillhöra ett tight och kompetent team bestående av fyra Data Scientists samt teamchefen Elin. Teamet arbetar tekniskt och analytiskt i SAS, SQL och Python, men de är långt ifrån det stelbenta analytikerteam du kanske föreställer dig. De är ett öppet, socialt och ganska extrovert gäng som har högt i tak, stöttar varandra i vardagen och gillar att hitta på roliga saker tillsammans.

Som person är du samarbetsinriktad, lösningsorienterad och transparent. Du bidrar positivt till stämningen i teamet, kommunicerar tydligt med olika intressenter och känner dig bekväm med att utmana antaganden när det behövs. Du trivs med att arbeta med komplexa frågeställningar, tar ägarskap för dina leveranser och har en stark känsla för kvalitet.

Du erbjuds

• En roll med stor påverkan på bankens framtida ramverk och metoder. I det stöttande teamet får du goda möjligheter att utvecklas tekniskt inom Python och SQL samtidigt som du bygger en djup förståelse för bankaffären.
• En visstidsanställning hos Academic Work där goda möjligheter till överrekrytering finns efter 6-12 månader. Vi erbjuder även fast månadslön.

Arbetsuppgifter

• Använda din analytiska förmåga till att hantera komplexa utmaningar och göra skillnad inom det affärskritiska området riskjusterad finansiell styrning.
• Bidra till utvecklingen av nya modeller och metoder för kapitalallokering och riskjusterad lönsamhetsstyrning inom den svenska företagsaffären.
• Arbeta med stora datamängder för att genomföra kvantitativa analyser och ta fram insikter för att förbättra modellprestanda.
• Tillämpa datadriven analys för att identifiera möjligheter till ökad kapitaleffektivitet och förbättringar av kapitalberäkningar.

Vi söker dig som

• Akademisk examen inom matematik, statistik eller industriell ekonomi.
• Goda kunskaper i SQL, R eller Python.
• God förmåga att utföra kvantitativ analys och datamodellering.
• Bekväm med att arbeta med stora och komplexa datamängder.
• Flytande kunskaper i svenska och engelska i både tal och skrift.

Det är meriterande om du har

• Erfarenhet från analytiska roller inom kreditrisk, modellering (IRB/IFRS 9), ICAAP, stresstester eller kapitalhantering.
• Tidigare erfarenhet av finansmatematik eller affärsstyrning inom bank.

För att lyckas i rollen har du följande personliga egenskaper:

• Hjälpsam
• Målmedveten
• Social
• Ansvarstagande
• Energisk
• Intellektuellt nyfiken

Vår rekryteringsprocess

Denna rekryteringsprocess hanteras av Academic Work och vår kunds önskemål är att alla frågor rörande tjänsten skickas till Academic Work.

Vi tillämpar löpande urval och kommer plocka ner annonsen när tillräckligt många kandidater har nått slutskedet i rekryteringsprocessen. Vid ansökan efterfrågas ett CV. Personligt brev använder vi inte som urvalsmetod och behöver därför inte bifogas. Rekryteringsprocessen innehåller två urvalstest: ett personlighetstest och ett test i kognitiv förmåga. Testerna är ett verktyg för att kunna hitta den kandidat med högst potential för tjänsten samt främja jämlikhet, mångfald och en rättvis rekryteringsprocess.