Projektledare för AI - Lediga jobb

Build the future of data platforms with Databricks at the core

Do you want to work with one of the market’s most powerful data platforms and deepen your expertise in data engineering? At Knowit, we are looking for a Databricks Specialist / Data Engineer who wants to help create scalable, modern data solutions – with Databricks and Python at the center.

About the role as a Databricks Specialist at Knowit

In this role at Knowit in Gothenburg, you will help our clients design, build, and orchestrate modern cloud-based data platforms. You will work with Databricks as the core of these solutions and have the opportunity to stay at the forefront by exploring new features, ways of working, and best practices within the platform.

You will be part of a strong competence network within Cloud, Data, and AI, where collaboration, knowledge sharing, and continuous technical development are a natural part of everyday work. As a selected Databricks partner, we work closely with the platform and continuously stay up to date with new capabilities.

Your main responsibilities will include:

• Designing and developing scalable data platforms based on Databricks and Lakehouse architecture

• Building, optimizing, and orchestrating data pipelines using Python and PySpark

• Working with data governance and management through Unity Catalog

• Integrating data with BI, AI, and ML solutions to create real business value

• Supporting clients in establishing secure, robust, and future-proof data engineering solutions

Our tech stack / tools and ways of working

• Data platform: Databricks

• Programming: Python, PySpark

• Cloud platforms: Azure, AWS, and Google Cloud

• Data architecture: Lakehouse, modern data platforms

• AI & Analytics: integrations with BI, AI, and machine learning

We believe in flexibility and continuous learning. You are not expected to know everything from day one – your willingness to grow is just as important as your current technical skills.

Who are we looking for?

We are looking for someone with a solid foundation in data engineering and several years of experience working as a Data Engineer in modern data environments. You have a genuine interest in Databricks and want to continue deepening your expertise within the platform and its ecosystem.

As a person, you are curious, solution-oriented, and enjoy tackling complex technical challenges. You have strong skills in Python and PySpark and are comfortable working with cloud-based data platforms. Experience with data governance and orchestration, for example using Unity Catalog, is a plus.

Previous experience in a consulting role is also considered an advantage, as well as an interest in or experience with AI and machine learning. You enjoy collaboration, knowledge sharing, and working closely with both colleagues and clients to create solutions that deliver real business value.

What does Knowit offer in Gothenburg?

At Knowit in Gothenburg, you will be part of a culture characterized by collaboration, curiosity, and technical excellence. You will work on exciting and varied projects across industries such as retail, finance, automotive, and manufacturing, where Databricks, Python, and modern data platforms are at the core.

We offer a high degree of flexibility in how you work and the opportunity to work with your preferred major cloud platform depending on client needs. At the same time, we invest long-term in your development through continuous learning, including training, certifications, and conferences.

You will be based at our modern office in Gothenburg, with the possibility of a flexible work setup, and become part of a company that values work-life balance – where you also get to help shape the future of data engineering together with Knowit.

Are you ready to shape the future of data platforms?

We believe the future of data engineering is Databricks-driven. Do you want to help shape it together with us at Knowit in Gothenburg?

Welcome to apply – we look forward to hearing from you!

Providing Value & Impact - SwedQ.

SwedQ is a consultancy company that has lately proven to have a unique model for those who want to grow, create a legacy, and take on challenges that both add and gain value. Year after year, we have managed to serve clients within a wide range of industries (intentionally excluding gambling and weaponry). During this time, we have also grown steadily—in revenue, in team size, and in the impact of our deliveries.

We are looking for someone who wants to be part of the company in a literal sense. That means taking on the technical challenges as well as getting a portion of the company in the future. If you would like, you can also drive your own ideas forward and implement them with us. You’ll be working closely with everyone here, which makes it easy to bring change and act on what you believe in.

What's in it for you? The question goes back to you: what do you want (with common sense or not)? Some people value fixed salaries, pensions, and stability. Others want a bigger share of the pie and are ready to share the risks. Let’s talk that through. One thing is certain—we’ll make sure you find your “it,” whether that’s with us in-house or with our clients.

We’ll shape the role to fit both your needs and ours. The good thing? You will be surrounded by people who are technically savvy, giving you plenty of opportunities to teach and learn. And if not technically, then perhaps in entrepreneurship. We know - it’s a lot of questions. That’s why we have interviews, right?

Who are you:

• At least 5 years of hands-on experience building, owning, and operating production-grade data pipelines in complex, data-intensive environments

• Strong experience designing and evolving batch-based ETL / ELT pipelines that power externally facing analytics products and dashboards used at scale

• Proven ability to transform raw event- and transaction-level data into trusted, business-critical KPIs, including funnel metrics, performance indicators, and customer insights

• Deep expertise in Python and advanced SQL, with a strong focus on analytical queries, feature engineering, and correctness at scale

• Experience automating and standardizing reporting workflows, replacing manual or semi-automated processes with robust, maintainable data products

• Strong understanding of data modeling, schema evolution, metric definitions, and data quality in analytical data warehouse environments

• Hands-on experience optimizing SQL-heavy pipelines, removing unnecessary transformation layers, and improving end-to-end data efficiency

• Experience collaborating closely with Product Analytics, Data Modeling, and Product Engineering teams to translate business needs into scalable technical solutions

• Familiarity with workflow orchestration and dependency management using tools such as Airflow (or equivalent schedulers)

• Experience working with batch and ELT-style pipeline patterns in modern data platforms

• Solid hands-on experience with AWS (e.g. S3, Redshift, IAM) and analytical data warehouses such as Redshift or similar

• Experience with CI/CD and production deployment best practices for data systems (e.g. Jenkins, Git-based workflows)

• Ability to take strong ownership of mission-critical data products, with a clear focus on reliability, scalability, and long-term maintainability

• Interest in building data platforms that go beyond reporting — enabling trend analysis, behavioral insights, performance measurement, and data-driven recommendations

• Experience from fintech, payments, or other regulated environments is a strong plus

• Strong analytical mindset, problem-solving skills, and the ability to clearly communicate complex data concepts to both technical and non-technical stakeholders

• Experience with basic front-end or visualization technologies (e.g. React) is a nice-to-have

• Fluent in English and Swedish

SwedQ culture SwedQ began with siblings who brought in people they knew. Those people recommended friends, and from there, the company grew further through open head-hunting. Over time, we’ve built a diverse team with different backgrounds, experiences, and insights.

We made sure to amplify this diversity by embracing independence and accountability while driving value-creating work. At the same time, we make sure to have fun—with epic football tournaments, unforgettable trips, and great dinners.

Perks & Benefits

• Competitive salary—you decide your preferred salary model

• Budget to spend on health and gym

• Generous developer budget

• Monthly payments into your additional pension fund

• Private health insurance

• Private healthcare

• Office in the city – a stone’s throw from public transport and lunch restaurants

• Breakfast in the SwedQ office EVERYDAY

• Support for open-source projects and community engagement

• Kick-ass colleagues and mentors at every corner

• Company car (or car allowance)

• Benefits to make life easier—home cleaning, childcare, and more

Vill du arbeta med integration på riktigt, från klassiska systemkopplingar till moderna, eventdrivna lösningar? Vill du dessutom ha stort ansvar, påverka teknikval och arbeta i en miljö där kvalitet går före volym?

Nu söker vi en senior integrationskonsult till ett växande specialistbolag inom integration, BI och AI.

Om rollen

Som senior integrationskonsult arbetar du end-to-end med integrationslösningar, från design till implementation och drift. Du blir en nyckelperson i uppdrag där du både bygger lösningar och fungerar som rådgivare mot kund.

Rollen är bred och affärsnära, där du har stort ansvar och möjlighet att påverka både tekniska beslut och arbetssätt.

Arbetsuppgifter

I rollen kommer du bland annat att:

• Design och utveckling av integrationslösningar

• Arbeta med API:er, meddelandeköer och filbaserade integrationer

• Bygga integrationsflöden i exempelvis Azure Integration Services

• Säkerställa robusta lösningar

• Rådgivning kring integrationsarkitektur och tekniska vägval

Vem vi söker

Vi söker dig som är en senior integrationskonsult med djup teknisk förståelse och erfarenhet av att designa, utveckla och driva integrationslösningar från start till mål.

• Har minst 5 års erfarenhet inom integration / systemintegration

• Har arbetat med integration mellan affärssystem

• Har stark teknisk förståelse (t.ex. REST, JSON, XML)

• Erfarenhet av CI/CD

• Är van att felsöka, arbeta med loggning och hantera driftfrågor

Meriterande

• Erfarenhet av Azure (Logic Apps, Service Bus, API Management, Functions)

• Erfarenhet av traditionella integrationsplattformar (t.ex. BizTalk)

• Erfarenhet av eventdriven arkitektur

• Kunskap inom säkerhet (OAuth2, certifikat, autentisering)

• Erfarenhet av kravarbete och kunddialog

För att lyckas i rollen tror vi att du är: Det som verkligen avgör i denna roll är att du:

Är självgående, ansvarstagande, kommunikativ och trygg i kunddialog. Vi tror att du är van att ta ägandeskap över hela leveransen. Som person är du lösningsorienterad med ett affärsmässigt driv.

Om företaget

Företaget är ett mindre specialistbolag med stark kompetens inom BI och dataplattformar. Här får du stor frihet och möjlighet att påverka ditt arbete. De arbetar med långa och stabila kunduppdrag i en kultur präglad av tillit, ödmjukhet och samarbete.

Ansökan

A-hub ansvarar för rekryteringsprocessen och samarbetar nära med vår kund i denna tillsättning. Har du frågor om rollen är du varmt välkommen att kontakta oss.

Vi arbetar löpande med urval, så skicka gärna in din ansökan så snart som möjligt.

Build modern data platforms with Databricks at the center

Do you want to work hands-on with Databricks and deepen your expertise in data engineering? At Knowit, we are looking for a Databricks Specialist / Data Engineer who wants to help build scalable, modern data solutions with Databricks and Python as a central part of the solution.

About the role as a Databricks Specialist at Knowit

In this role at Knowit Lakehouse in Stockholm, you will help our clients design, build, and orchestrate modern cloud-based data platforms. Databricks will be a key part of these solutions, and you will have the opportunity to explore new features, approaches, and best practices within the platform.

You will join a strong competence network within Cloud, Data, and AI, where collaboration, knowledge sharing, and ongoing technical development are part of everyday work. As a Databricks partner, we work closely with the platform and stay up to date with new capabilities.

Your main responsibilities will include:

• Designing and developing scalable data platforms based on Databricks and Lakehouse architecture

• Building, optimizing, and orchestrating data pipelines using Python and PySpark

• Working with data governance and management through Unity Catalog

• Integrating data with BI, AI, and ML solutions to create real business value

• Supporting clients in establishing secure, robust, and future-proof data engineering solutions

Our tech stack / tools and ways of working

• Data platform: Databricks

• Programming: Python, PySpark

• Cloud platforms: Azure, AWS, and Google Cloud

• Data architecture: Lakehouse, modern data platforms

• AI & Analytics: integrations with BI, AI, and machine learning

We believe in flexibility and continuous learning. You are not expected to know everything from day one your willingness to grow is just as important as your current technical skills.

Who are we looking for?

We are looking for someone with a solid foundation in data engineering and several years of experience working as a Data Engineer in modern data environments. You have a genuine interest in Databricks and want to continue deepening your expertise within the platform and its ecosystem.

As a person, you are curious, solution-oriented, and enjoy tackling complex technical challenges. You have strong skills in Python and PySpark and are comfortable working with cloud-based data platforms. Experience with data governance and orchestration, for example using Unity Catalog, is a plus.

Previous experience in a consulting role is also considered an advantage, as well as an interest in or experience with AI and machine learning. You enjoy collaboration, knowledge sharing, and working closely with both colleagues and clients to create solutions that deliver real business value.

About us At Techrytera AB, recruitment starts with you. We are a staffing and recruitment company with deep expertise and a clear focus on IT and Engineering. With our industry knowledge and close dialogue with both candidates and clients, we create precise matches where the right skills meet the right needs.

We believe that a truly great match is not just about a job description – it’s about your experience, your potential, and what you genuinely want to develop in. That’s why we always focus on the individual. By understanding your background, motivations, and ambitions, we can connect you with assignments and roles at our clients where you have the right conditions to grow and make an impact.

Our goal is to build long-term and meaningful collaborations – for both you as a candidate and for our clients.

Job Description Required Skills & Technologies

Core Programming & Development

1. Python (3.9-3.11) - Primary language; requires solid. Senior proficiency

2. Object-Oriented Programming - Complex class hierarchies, inheritance patterns

3. Multiprocessing & Concurrency - Process management, queues, events, threading

4. Worked with Enterprise software for Automotive

5. Production ETL pipeline experience

6. Automotive/testing industry knowledge

7. Complex distributed system design experience

Data Engineering & ETL

1. ETL/ELT Pipelines - Core focus of the repository

2. Data Processing - Large-scale test bed data ingestion

Sympathy for Data - Domain-specific data processing framework (key requirement)

File Processing - Multiple formats (.sydata, .h5, various test data formats)

Cloud & Infrastructure

1. Azure Experience

Windows Server - Deployment target environment

GitHub Actions - CI/CD pipelines

Poetry

Database Technologies

Oracle Database

SQL

MongoDB

Specialized Knowledge

Test Bed Systems - Automotive testing domain knowledge

Additional Technical Skills

Windows-specific:

• PowerShell scripting

• Windows service deployment

Logging & Monitoring, on file system level and to Grafana

Network & File Systems:

• Network drive mounting

• SMB/CIFS protocols

• NAS interactions Application

When you apply through Techrytera AB, you’re not just applying for a job – you’re starting a dialogue about your career path. We want to get to know you, your experience, and your ambitions so that we can match you with the right opportunities at our clients.

Does this sound interesting? Submit your application or get in touch with us to learn more. We look forward to discovering the next step in your career together with 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, 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.

• 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.

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.

Öppen för alla Vi fokuserar på din kompetens, inte dina övriga förutsättningar. Vi är öppna för att anpassa rollen eller arbetsplatsen efter dina behov.

Om oss På Techrytera AB börjar rekryteringen med dig. Vi är ett bemannings- och rekryteringsföretag med spetskompetens och ett tydligt fokus inom IT och Engineering. Med vår branschkunskap och nära dialog med både kandidater och kunder skapar vi träffsäkra matchningar där rätt kompetens möter rätt behov.

Vi tror att en riktigt bra matchning inte bara handlar om en rollbeskrivning – utan om dina erfarenheter, din potential och vad du faktiskt vill utvecklas inom. Därför utgår vi alltid från individen. Genom att förstå din bakgrund, dina drivkrafter och dina ambitioner kan vi koppla ihop dig med uppdrag och roller hos våra kunder där du får rätt förutsättningar att utvecklas och göra skillnad.

Vårt mål är att bygga långsiktiga och meningsfulla samarbeten – både för dig som kandidat och för våra kunder.

Arbetsbeskrivning

Rollen som BI-utvecklare (Dataingenjör) i projekt och förvaltningar kan bl.a. omfatta följande

uppgifter:

• I datalagret, designa och utveckla procedurer, databasscheman och logik skrivet i SQL för Microsoft SQL Server

• Ansvara för acceptanstest mot slutanvändare

• I ett DevOps-team förvalta och vidareutveckla leveranser till slutanvändare bl.a. för våra Machine learning algoritmer, där både historiska data och data i realtid ingår

• Ta fram eller uppdatera systemdokumentation

• Samarbete inom teamet men även med andra delar av organisationen.

• Förekommande förvaltning så som hantera incidenter, där felsökning och buggrättning kan ingå, samt bistå i övrigt i IT-förvaltningen av våra applikationer.

• Ha förmåga att agera som scrum master för det agila teamet: koordinera det dagliga arbetet

samt förvalta backloggen i samråd med produktägare

Skallkrav

1. Utbildning / erfarenhet Högskole-/universitetsutbildning om minst 120p/180hp inom IT, eller minst 15 års relevant arbetslivserfarenhet som bedöms likvärdig.

2. SQL-utveckling Minst 5 års erfarenhet (inom de senaste 10 åren) av arbete med SQL-utveckling.

3. SQL Server prestandaoptimering Minst 10 års erfarenhet av prestandaoptimering i SQL Server, inklusive analys, felsökning och förbättring av komplexa databassystem.

4. Avancerad SQL-programmering Minst 10 års erfarenhet av SQL-programmering, inklusive skrivning, granskning och optimering av avancerad SQL-kod.

5. Data Engineer-roll Minst 10 års erfarenhet som Data Engineer i medelstora organisationer (200+ anställda).

6. Agil systemutveckling Minst 5 års erfarenhet av arbete i agil IT-organisation med agil systemutveckling.

7. Stora datamängder och datakällor Minst 10 års dokumenterad erfarenhet (inom de senaste 15 åren) av arbete med:

• Stora datamängder och komplexa datamodeller

• Flera datakällor, både strukturerade och ostrukturerade

8. Databaser och databasarkitektur Minst 10 års dokumenterad erfarenhet (inom de senaste 15 åren) av:

• Datamodellering

• Databasdesign

• Prestandaoptimering och tuning av relationsdatabaser och moderna datalagringslösningar

9. ETL-processer Minst 10 års dokumenterad erfarenhet (inom de senaste 15 åren) av:

• ETL-processer (Extract, Transform, Load)

• Utveckling, automatisering och optimering av datainflöden

10. Data pipelines och orkestrering Praktisk erfarenhet av data pipelines och orkestreringsverktyg, exempelvis:

• Microsoft SQL Server Integration Services (SSIS)

• Azure Data Factory

• eller motsvarande verktyg

11. Test, felsökning och datavalidering Minst 10 års dokumenterad erfarenhet av att testa, felsöka och validera datamängder.

Mervärdeskrav

1. Kraftsystem / energiverksamhet Erfarenhet av minst ett uppdrag inom verksamhet som arbetar med kraftsystem under de senaste 8 åren.

2. BI-verktyg Erfarenhet av minst ett uppdrag inom Power BI eller annat BI-verktyg under de senaste 8 åren.

Ansökan När du söker via Techrytera AB söker du inte bara ett jobb – du påbörjar en dialog om din fortsatta karriär. Vi vill lära känna dig, din erfarenhet och dina ambitioner för att kunna matcha dig med rätt möjligheter hos våra kunder.

Låter det intressant? Skicka in din ansökan eller hör av dig till oss så berättar vi mer. Vi ser fram emot att hitta nästa steg i din karriär tillsammans med dig.

TL;DR

→ You own the data layer, ingestion, transformation, and modeling that makes analytics, reporting and AI possible.

→ Consultant role across the Nordics, with clients spanning industries from financial services to manufacturing.

→ You work in cross functional delivery teams alongside Platform, Analytics and GenAI Developers, each owning a distinct layer of the stack.

→ Certifications without a debate. Colleagues who are obsessed with the craft. Freedom to grow your way.

What you'll do

As a Data Engineer, you’ll be building the data platforms that everything else depends on. From raw source systems to production-ready models consumed by analysts, ML pipelines, and business users. You own the path data takes to become useful. The work is hands-on Python and SQL, heavy on PySpark, and grounded in Kimball modeling and lakehouse architecture.

You come in before the solution is defined. Together with the client, you shape what gets built, then you build it. You'll work in cross-functional delivery teams alongside platform engineers and AI developers, each owning a distinct layer of the stack.

A few examples of what this looks like in practice:

• Building a Kafka-based ingestion framework for a major insurance group, onboarding several thousand tables at scale so multiple downstream teams can actually use the data they need.

• Lifting an on-prem data warehouse into a cloud-based Databricks lakehouse for a Nordic logistics company, standing up CI/CD, integration, modeling, and quality assurance, then scaling for new use cases.

• Auditing a manufacturing company's data platform against best practices, delivering a migration plan, then staying on to bring in new sources, optimize workflows, and build out analytics models.

The bar for what "done" means here is high: production-grade, observable, secure and used.

What you get

Assignments that accelerate you. Every 6–18 months you're in a new engagement. New industry, new architecture decisions, new stakeholders to earn trust from. You'll face more distinct technical challenges in two years here than most engineers see in five.

Work that's hard to come by elsewhere. Modern data platforms underpinning enterprise AI is one of the most technically demanding spaces right now. The problems here aren't solved yet, and you'll be among the people solving them.

Your direction, your call. Want to go deep technically, specialise in Databricks and Spark engineering, platform foundations or analytics engineering? Go for it. Want to grow toward Tech Lead or Solution Architect, steering delivery and building long-term client relationships? Also go for it. Both paths are real and equally valued.

People who make you better. The people here are genuinely passionate about technology, not as a job, but as something they care about. Engineers who go deep because they want to, follow the space obsessively, and get restless when things stop moving. That's what keeps Redeploy consistently ahead, and it's what you'll feel from day one.

The Perks. 30 days vacation · hybrid work and flexible hours · private medical insurance · pension (ITP1) · wellness allowance 5,000 SEK · free choice of tools and tech · free breakfast, soda and snacks · yearly gatherings and AW's · a team with genuine interests outside work — gaming, food, running, padel, golf, football, cycling

Who you are

You take ownership, hold yourself to a high standard, and bring real opinions to the table. You communicate clearly with both technical and non-technical stakeholders, and you're energised by the consulting pace, new challenges, new contexts, and the pressure to deliver.

We care more about how you think, build and collaborate than whether your background ticks every box. Maybe you come from software development and want to move closer to data. Maybe you've never worked in consulting but you're curious about the variety it brings. Humble enough to play for the team, sharp enough to push back when it matters.

What you bring

• A background in Computer Science, IT, Engineering or equivalent university degree

• Strong programming skills in Python, with solid experience in SQL and Spark, and a sound understanding of software engineering principles

• Experience with cloud-based data solutions (Azure preferred, but AWS is also highly relevant)

• Solid understanding of data structures, modeling and processing

• Familiarity with data architectures like Lakehouse and Medallion

• AI-assisted development (you actively use tools like Claude Code, Codex, or similar in your daily work)

Strong plus: Databricks or Microsoft Fabric, CI/CD pipelines for data, data governance, graph databases, prior consulting experience, Swedish language skills

About Redeploy

Redeploy is where cloud, data, and AI come together in production. We help Nordic enterprises design, build, and operate modern tech platforms and AI solutions that are secure, scalable, and production-ready. Engineers at heart, we work hands-on across Azure, AWS, and Databricks from strategy to operations.

Om oss På Techrytera AB börjar rekryteringen med dig. Vi är ett bemannings- och rekryteringsföretag med spetskompetens och ett tydligt fokus inom IT och Engineering. Med vår branschkunskap och nära dialog med både kandidater och kunder skapar vi träffsäkra matchningar där rätt kompetens möter rätt behov.

Vi tror att en riktigt bra matchning inte bara handlar om en rollbeskrivning – utan om dina erfarenheter, din potential och vad du faktiskt vill utvecklas inom. Därför utgår vi alltid från individen. Genom att förstå din bakgrund, dina drivkrafter och dina ambitioner kan vi koppla ihop dig med uppdrag och roller hos våra kunder där du får rätt förutsättningar att utvecklas och göra skillnad.

Vårt mål är att bygga långsiktiga och meningsfulla samarbeten – både för dig som kandidat och för våra kunder.

Arbetsbeskrivning Vi söker en erfaren och analytisk Data Engineer som vill arbeta med att förstå och optimera vår kunds datatransaktioner.

Som Data Engineer blir du en nyckelperson i vår kunds team och ansvarar för att analysera, strukturera och förbättra deras interna dataprocesser och kopplingar mellan system. Du kommer att arbeta med stora datamängder, bygga effektiva pipelines och säkerställa datakvalitet för att stödja verksamhetens behov.

Vår kunds vision är att ta en ledande position på elmarknaden och bygga stabila, datadrivna lösningar som bidrar till ett hållbart energisystem. Nu behöver de din hjälp för att komma dit.

Dina ansvarsområden

• Analysera och förstå datatransaktioner mellan våra system.

• Utveckla och optimera datamodeller, pipelines och integrationer.

• Arbeta med databaser som MSSQL, Oracle, Snowflake och verktyg som DBT.

• Säkerställa datakvalitet, prestanda och tillgänglighet.

• Samarbeta med utvecklare, analytiker och verksamheten för att skapa effektiva datalösningar.

Nödvändiga färdigheter

• Dokumenterad erfarenhet av SQL och arbete med relationsdatabaser.

• Erfarenhet av databaser som MSSQL, Oracle, Snowflake.

• Kunskap om ETL-processer och dataintegration.

• Förståelse för datamodellering och optimering av databaser.

• Erfarenhet av att arbeta med DBT eller liknande verktyg för data transformation.

• Grundläggande förståelse för dataskydd och säkerhet.

Meriterande färdigheter

• Erfarenhet av Python eller andra språk för datahantering.

• Kunskap om molnplattformar (Azure, AWS eller GCP).

• Erfarenhet av dataanalys och visualisering.

• Arbetat med IoT, MQTT och realtidsdata samt förstå konsekvenserna av bearbetning av realtidsdata för analys

• Vana att arbeta i agila team och med DevOps-principer.

Ansökan När du söker via Techrytera AB söker du inte bara ett jobb – du påbörjar en dialog om din fortsatta karriär. Vi vill lära känna dig, din erfarenhet och dina ambitioner för att kunna matcha dig med rätt möjligheter hos våra kunder.

Låter det intressant? Skicka in din ansökan eller hör av dig till oss så berättar vi mer. Vi ser fram emot att hitta nästa steg i din karriär tillsammans med dig.

The Data Engineer role exists to ensure that all test‑lab data is trustworthy, accessible, scalable, and usable for engineering, validation, analytics, and decision‑making. The function provides the technical backbone that enables reliable testing, advanced analysis, automation, and long‑term product improvement.

The Data Engineer is responsible for designing and operating the data infrastructure that supports all laboratory test activities. This includes connecting test equipment, building pipelines for high‑frequency and large‑volume datasets, ensuring data quality, and enabling engineers, analysts, and scientists to work efficiently with accurate data.

As the laboratory and organization expand, the role will evolve into a leadership function that guides the long‑term data strategy and leads a multidisciplinary data team.

Key Responsibilities

Key responsibilities include (but are not limited to)

• Design, build, and maintain data pipelines for high‑frequency lab data

• Integrate test equipment such as battery cyclers (Chroma, Keysight, PEC, PNE), chambers, DAQ systems, and PLCs

• Develop ETL/ELT processes to transform raw → validated → curated datasets

• Build scalable data storage solutions (data lakes, time-series DBs, structured metadata stores)

• Implement data validation, anomaly detection, and quality monitoring

• Automate data processing for reporting, dashboards, and analysis

• Ensure data traceability, version control, and audit compliance

• Work closely with test and validation engineers to understand test profiles, metadata, and measurement methods
• Support lab technicians with tools that simplify workflows and reduce manual data tasks

• Integrate with MES, LIMS, PLM, and other enterprise systems

• Troubleshoot data-related issues in test execution or equipment communication

• Take increasing ownership of data architecture and long‑term data roadmap

• Contribute to documentation standards, data governance, and best practices

Requirements

Qualifications and Experience

• Engineering in technical data role (Data Engineering, Data Science, Machine Learning) including processing, storage, quality, and management on GCP or AWS

• +4 years of relevant experience

• Project management experience

• Experience in large manufacturing or industrial enterprises with heterogeneous, distributed data sources, demonstrating ability to navigate complexity at scale

Specific skills & Knowledge

• Proven experience scaling and re‑architecting data platforms and infrastructure to handle rapid growth and increasing data volumes

• Hands-on experience designing and building highly scalable and reliable data architectures using modern cloud and data tooling (e.g., AWS Kinesis, Lambda, Redshift, GCP equivalents; Airflow, dbt; Parquet, Protobuf, Avro)

• Strong programming skills in Python, SQL, and general-purpose scripting for automation, data processing, and integration

• Deep understanding of ETL/ELT frameworks (Airflow, dbt, Spark, etc.) and experience building production-grade data pipelines

• Familiarity with time-series and high‑frequency measurement data, particularly from industrial or test environments

• Cloud engineering experience in AWS, GCP, or Azure, including serverless architectures, distributed storage, and stream processing

• Experience with CI/CD, Git-based workflows, Docker, and robust software engineering practices

• Knowledge of data serialization formats (Parquet, Avro, Protobuf, JSON) and best practices for efficient storage and retrieval

• Experience integrating systems via APIs; familiarity with hardware communication protocols such as REST, OPC-UA, and Modbus is a strong plus

• Understanding of machine learning concepts and experience supporting data scientists with structured, high-quality datasets

Domain knowledge (Preferred)

• Solid engineering foundation (electrical, mechanical, chemical, physical), preferably within the energy, electrical testing, or battery domain

• Understanding of sensor calibration, noise, drift, and data validation