Agil coach - Lediga jobb

Studies show that women and underrepresented groups often hesitate to apply unless they meet every requirement. At Stegra, we’re building an impact-driven, sustainable company - and we need a diverse, inclusive team to make it happen.

If you share our passion but don’t meet every qualification, we encourage you to apply anyway. You might be the perfect fit for this role, or another as we grow.

At Stegra, we’re not just building a plant, we’re proving that sustainable industry is possible. And to do that, we need people like you.

Join a team where safety comes first. Where we support each other, learn as we go, and make space for everyone to grow and contribute. This is your chance to be part of something big - while being closer to nature and leading a balanced, purposeful life.

What you’ll do

We are building a next-generation steel plant - and data is a core part of how we operate, optimize, and scale. We believe the best data solutions are created close to the business, by teams who understand both the context and the technology. We are now looking for a Data Engineer to join our Digital Domain supporting Finance and HR. In this role, you will work at the intersection of business and technology - helping shape how data is modeled, shared, and used to drive decisions across the organization. You will be part of a cross-functional team where business experts, analysts, and developers collaborate closely.

Together, you will build data products that are reliable, understandable, and designed to be reused across the company - not just for a single use case. At the same time, you will contribute to how we build our data platform and ways of working. We aim to continuously evolve - adapting to new technologies, improving how we design data, and staying aligned with modern best practices. You will also take a leading role in facilitating the data platform roadmap - aligning needs across domains, shaping priorities, and ensuring progress on key initiatives.

Responsibilities:

• Design, build, and maintain data pipelines and products that enable Finance and HR to make reliable, data-driven decisions
• Work closely with business stakeholders and analysts to translate needs into scalable data models and solutions
• Help structure and expose data so it is consistent, understandable, and reusable across domains · Take an active role in improving how we work with data across teams - leading and driving improvements to platform capabilities, standards, and patterns
• Enable self-service use of data by making it accessible and usable beyond engineering teams
• Make thoughtful trade-offs in how data is designed and delivered - balancing batch vs near-real-time, handling historical data, and shaping metrics and semantics for usability
• Define and promote best practices for data quality, testing, documentation, and access control
• Explore how modern tooling, including AI-assisted development, can improve how we build, test, and maintain data products
• Support and coach colleagues in modern data engineering practices

What you’ll bring

You enjoy solving real problems and are motivated by building data solutions that are actually used. You are curious about how data platforms should be designed — and how those designs need to evolve as technology and business needs change.

We believe you bring many of the following:

• Several years of experience in data engineering or modern data platform development
• Experience building end-to-end data solutions (ingestion, storage, transformation, consumption)
• Interest in contributing beyond your immediate team — shaping shared ways of working, standards, and platform capabilities
• Strong SQL skills and experience modeling data for analytical use
• Experience with cloud-based data platforms and infrastructure-as-code
• Knowledge of engineering practices such as CI/CD, testing, and code review
• Ability to make sound technical decisions without being tied to specific tools or vendors
• Interest in areas such as self-service analytics, semantic modeling, temporal data, and data governance
• Experience working closely with business stakeholders, analysts, or operational teams
• Strong communication skills and ability to explain technical solutions clearly

Nice to have:

• Experience with, or interest in, industrial/operational (OT) data and how data from physical processes can be used for analytics and optimization

Benefits at Stegra

At Stegra, you’ll join a company where your work has real impact on the climate, the industry, and future generations. We’re building a culture rooted in safety, trust, and inclusion, where people feel supported to grow and thrive.

Here’s what makes this role unique:

• Breadth, not silos: You’ll work across multiple technical areas - data, architecture, infrastructure and backend - gaining deep understanding of our digital ecosystem.
• Ownership from day one: You’ll support a specific domain and act as a bridge between operations and tech, and drive solutions all the way from need to implementation and iteration.
• Close to the action: You’ll collaborate closely with stakeholders, understand their workflows, and ensure your digital solutions create real value in their day-to-day operations.

This is Stegra

Stegra is on a mission to change the global steel industry by producing green hydrogen, iron, and steel - with the goal of eliminating CO₂ emissions. Instead of coal, we use green hydrogen and fossil-free electricity, meaning our primary emissions will be water and heat.

By 2030, our ambition is to produce 5 million tonnes of green steel annually in our fully integrated, digitized, and sustainable plant in Boden, Northern Sweden - currently under construction. But this is just the beginning. Our expertise in green hydrogen will enable us to decarbonize industries beyond steel, paving the way for a cleaner future.

Our Stockholm Office

Our modern Stockholm office is located on Norra Stationsgatan, close to Karolinska University Hospital in central Stockholm. Here, you’ll find a bright, collaborative workspace where cross-functional teams connect, share ideas, and drive progress. Whether you're visiting regularly or working hybrid, you'll be part of a vibrant office culture with easy access to the city’s energy and amenities.

What will you do?

As a Data Engineer at Rebtel, you will do more than build pipelines; you'll help shape the future of our data platform and influence how data is used across the company. At Rebtel, data sits at the heart of how we build products, understand customers, optimize growth, and make decisions.

This is a hands-on engineering role with significant ownership. You'll work across our modern data stack, build scalable data products, and help define the architecture that supports analytics, automation, and future AI initiatives.

If you're excited by clean architecture, modern data engineering practices, and solving meaningful business problems at scale; if you care about data quality and believe trust in data is built through engineering discipline; if you enjoy solving complex problems and turning ambiguity into practical solutions; and if you're excited to experiment with new technologies and approaches, we'd love to talk.

Areas of ownership:

• Design, build, and maintain scalable, reliable data pipelines that power our Snowflake data platform

• Integrate data from a wide range of business and product systems

• Enable data activation across customer-facing and operational platforms, including CRM, customer support, and marketing tools

• Develop robust monitoring, alerting, and observability practices to ensure platform reliability

• Troubleshoot, optimize, and continuously improve data workflows and platform performance

• Design and implement scalable ELT workflows using modern data engineering practices

• Build well-structured dimensional models (facts and dimensions) that enable self-service analytics and reporting

• Implement automated testing and quality controls throughout the data lifecycle

• Ensure data is accurate, accessible, and trusted across the organization

• Work closely with analysts, product managers, engineers, marketers, and business stakeholders to understand data needs and deliver impactful solutions

• Help translate complex business challenges into scalable data products and datasets

• Support decision-making by making data easier to discover, understand, and use

• Evaluate emerging technologies, frameworks, and industry best practices

• Run proof-of-concepts and contribute to strategic technology decisions

• Help define the future architecture of Rebtel's data platform

• Continuously improve engineering standards, tooling, and developer experience

Requirements:

• You are an excellent communicator and collaborator. We work in English, but you will hear many languages in our Stockholm office

• 3+ years of experience in Data Engineering or a similar role

• Strong SQL skills and experience building production-grade data pipelines

• Experience with modern ELT methodologies and data warehousing concepts

• Experience integrating data from multiple systems and sources

• Experience with dbt, Python, AWS, or similar cloud-based data platforms

• Strong understanding of data modeling and analytics engineering best practices

• Ability to operate independently and take ownership of technical solutions

• Experience working in fast-growing technology or digital product companies is a plus

• It's a bonus if you've been exposured to customer analytics, marketing analytics, experimentation, or machine learning workflows

• Experience with BI tools such as Looker, Tableau, or Power BI is a plus

• It's a plus with a degree in Computer Science, Engineering, Mathematics, or a related field

Why Rebtel?

Rebtel has been connecting people across borders for nearly 20 years. Today, we’re profitable, growing, and at a pivotal moment in our journey. As we enter our next phase, we’re building an organisation designed for speed, ownership, and real impact, where every role contributes directly to shaping what comes next.

This is a place with global ambition and a strong foundation, where ideas move quickly and decisions matter. You won’t get lost in layers of process or slow-moving structures. Instead, you’ll find the space to take ownership, collaborate across teams, and make meaningful contributions from day one. Based in Stockholm, we bring together a diverse, international team united by a shared purpose: to simplify the way people connect worldwide.

At Rebtel, you are the most important asset and we strive to provide a comprehensive package of benefits and perks that enhance your well-being and work experience. Here are some of the things you can expect from us:

• Pension Plan

• Health Checkups, Influenza shots and Private Medical Insurance

• Dental Insurance

• Occupational insurance

• Wellness allowance (5,000 SEK)

• Discount on gym memberships

• Bonus program

• Extra parental pay

• 30 days annual vacation

• Monday breakfasts

• Relocation Support, if you're joining us from afar, we'll assist you in making a smooth transition.

We are Rebtel. We come from all around the world to create products for anyone who has crossed a border. We believe in equal opportunity and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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

Vilka är Predictly? 

Predictly är ett konsultbolag som arbetar med allt från molnteknik (Google Cloud, AWS och Azure), data engineering och avancerad analys till fullstackutveckling, integration, AI-lösningar och infrastruktur som kod.

Hos Predictly får du arbeta nära seniora kollegor med djup kompetens genom hela systemutvecklingens livscykel och ta del av skräddarsydd kompetensutveckling baserad på dina mål och intresseområden. I kombination med generösa Work/Life-balance-policys och ett modernt kontor på Birger Jarlsgatan i centrala Stockholm erbjuder vi en arbetsmiljö där både människor och teknik får utrymme att växa. 

Vad ingår i rollen? 

Som Data Engineer på Predictly har du en nyckelroll i att bygga moderna dataplattformar i Google Cloud – från första arkitekturskiss till färdig leverans. Du arbetar nära kunderna och tar ofta helhetsansvar för plattformens tekniska uppsättning, inklusive IAM, datainsamling, strukturering och förädling av data för olika behov. 

Du utvecklar och underhåller robusta datapipelines med verktyg som Airflow, och BigQuery blir en central komponent i ditt dagliga arbete. Rollen är bred och kombinerar teknik, arkitektur och problemlösning i en dynamisk miljö där du kontinuerligt utmanas och utvecklas. Predictly samarbetar främst med medelstora kunder, där teamen ofta ansvarar för hela lösningen, något som ger dig stor möjlighet att påverka och skapa verkligt värde. 

Vem är du? 

För att lyckas i rollen tror vi att du har: 

• En relevant eftergymnasial utbildning 

• Minst 2–3 års erfarenhet av Molnplattformar, särskilt inom data engineering 

• Kunskap inom Data Warehouse och molnbaserade dataplattformar 

• Erfarenhet av att bygga och underhålla datapipelines 

• Förmåga att arbeta brett i teknikstacken, från arkitektur till implementation 

• Goda kunskaper i både svenska och engelska 

• EU-medborgarskap 

Vi tror att du känner dig trygg i utvecklarrollen och är lika självklar framför datorn som i ett modernt kontorslandskap. Du tar gärna ansvar för helheten hos kund och trivs i tvärfunktionella team där du snabbt anpassar dig till nya tekniska utmaningar. 

Det är meriterande om du har: 

• Förståelse för, eller erfarenhet av, DBT (Data Build Tool) 

• Arbetat genom olika faser av utvecklingsprojekt, från krav till förvaltning 

• Erfarenhet av agila arbetssätt 

Om du läst ända hit är chansen god att du är precis den vi söker. Vi ser fram emot att ta del av din ansökan! 

Så här ser rekryteringsprocessen ut 

Om du inte går vidare i just denna rekrytering behåller vi gärna dina uppgifter för framtida möjligheter som bättre matchar din profil.  

Urval sker löpande och tjänsten kan komma att tillsättas innan sista ansökningsdag. 

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.

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.

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.

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.

Forma framtidens datadrivna lösningar i molnet. Är du en erfaren Data Engineer som vill arbeta nära tekniken och bygga robusta dataplattformar i moderna molnmiljöer? Hos Knowit i Göteborg får du möjlighet att ta ett tekniskt ledarskap i uppdrag där kvalitet, skalbarhet och affärsvärde står i centrum – tillsammans med några av Sveriges mest datatunga myndigheter och företag.

Som Senior Data Engineer hos oss i Göteborg arbetar du med att designa och utveckla avancerade datalösningar i molnet. Du kommer arbeta med moderna principer inom datamodellering, semantic layers och data governance för att skapa robusta och framtidssäkra dataplattformar. Du tar ansvar för arkitekturval, implementation och optimering av pipelines, och fungerar som en teknisk förebild i teamet. Våra uppdrag spänner över både offentlig och privat sektor, där du är med och skapar lösningar där data blir en strategisk tillgång och en central del av verksamheten.

• Designa och implementera skalbara dataplattformar i moln (Azure, AWS, GCP)

• Bygga och optimera datapipelines med Python och DBT

• Säkerställa hög datakvalitet, prestanda och robusthet i komplexa system

• Driva tekniska beslut och bidra till best practices inom data engineering

• Stötta team och kunder i arkitektur- och designfrågor

• Python, SQL

• Dagster, Airflow

• DBT, Docker, Kubernetes

• Snowflake, DataBricks, BigQuery

• Molnplattformar: Azure, AWS, Google Cloud

• CI/CD och Infrastructure as Code

Vi uppmuntrar ständig teknisk utveckling och du får vara med och påverka både teknikval och arbetssätt i våra kunduppdrag.

Vi söker dig med minst 7 års erfarenhet som Data Engineer, som är redo att ta ett större ansvar i team och leveranser. Du har gedigen erfarenhet av molnbaserade lösningar, Python och DBT, och är van vid att arbeta nära både teknik och affär.

Du är trygg i att leda tekniska diskussioner, fatta beslut och stötta andra. Samtidigt är du prestigelös och trivs i en kultur där samarbete och lärande står i fokus. Erfarenhet av AI och datadrivna organisationer är ett plus.

Hos oss får du arbeta i uppdrag som gör verklig skillnad – från samhällsviktiga initiativ inom offentlig sektor till innovativa lösningar i industrin. Du får möjlighet att arbeta med välkända organisationer och myndigheter i en miljö där teknik, lärande och balans står i fokus. Vi erbjuder flexibilitet, ett centralt kontor i Göteborg och en kultur präglad av kunskapsdelning kultur, innovation, hållbarhet och en sund balans mellan arbete och privatliv. Vi har ett modern kontor i centrala Göteborg där vi ofta har aktiviter så som AW, föreläsningar och hackathons.

Välkommen med din ansökan och bli en del av Knowit i Göteborg!

Machine Learning Engineer

Leapit Consulting - Malmö, Sweden

About the role

Leapit is looking for experienced Machine Learning Engineers to join our growing engineering team in Sweden. We work with leading international companies across technology, finance, telecom, automotive, retail, and digital products.

As a Machine Learning Engineer, you will design, build, and deploy machine learning solutions that solve real business problems at scale. You will work end-to-end, from data exploration and experimentation to model development, production deployment, and continuous improvement.

You will collaborate closely with software engineers, data engineers, product teams, and business stakeholders to transform large and complex datasets into intelligent, production-ready solutions.

This role is ideal for engineers who combine strong data science skills with solid software engineering practices and enjoy working in modern, fast-moving development environments.

Responsibilities

• Design, develop, and deploy machine learning models for production systems
• Build scalable data pipelines and software solutions for large datasets
• Perform data analysis, feature engineering, and model evaluation
• Develop predictive models, anomaly detection systems, classification models, and NLP solutions
• Work with LLMs, prompting techniques, and agent-based workflows
• Integrate machine learning models into existing applications and cloud platforms
• Optimize model performance, scalability, and reliability
• Own technical deliveries from experimentation to production
• Collaborate with cross-functional teams including engineering, product, and business stakeholders
• Contribute to architecture, technical documentation, and best practices

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Data Science, or related field
• 5+ years of software engineering or machine learning experience
• Strong programming skills in Python
• Proven experience in machine learning and data science
• Experience with supervised and unsupervised learning methods
• Experience working with LLMs and modern AI workflows
• Strong knowledge of machine learning frameworks such as PyTorch, TensorFlow, Scikit-learn, NumPy, and Pandas
• Experience building and deploying production-grade machine learning systems
• Strong analytical and problem-solving skills
• Excellent communication skills in English