Data Engineer med modern stack (Databricks, Azure Data Factory & Azure)

Join a forward-thinking team shaping the future of HR Analytics. Work with a modern Azure and Databricks stack to deliver high-impact data solutions across Sweden and the Baltic states in a dynamic banking environment. About the role As a Data Engineer in this role, you will combine technical expertise with business understanding to develop our client's HR Analytics platform. You will primarily work on building and maintaining data models in Databricks using PySpark and SQL. You will also oversee and further build upon automated workflows in Databricks Workflows. The key competencies for this position also include Kimball modeling, practical application of SCD1 & SCD2, and experience with code management via Azure DevOps. You are offered We offer a high-impact hybrid role where you can work with the latest cloud technologies like Databricks and Azure, while enjoying the flexibility of a modern workplace environment. Work tasks This role focuses on the technical development and orchestration of data within an HR Analytics environment, utilizing Azure and Databricks to process complex HR data sets. Develop and maintain PySpark and SQL notebooks within Databricks on a daily basis. Implement and manage SCD1 and SCD2 Configure Unity Catalog for data governance, including catalogs, grants, and security. Manage CI/CD processes using Azure DevOps repos and YAML pipelines. Monitor Databricks Workflows and task dependencies. Collaborate on Power BI semantic models. We are looking for Advanced knowledge of Databricks, including PySpark and SQL. Strong experience with Delta Lake operations such as MERGE. Proficiency in designing Kimball star schemas and SCD1/SCD2. Solid understanding of Azure DevOps, YAML pipelines, and PR processes. Professional fluency in English and Swedish. It is meritorious if you have Knowledge of Oracle HCM or PeopleSoft data models. Experience with Power BI import mode and semantic models. Familiarity with Azure ADLS Gen2 Our recruitment process This recruitment process is handled by Academic Work and it is our client’s wish that all questions regarding the position is directed to Academic Work. Our selection process is continuous and the advert may close before the recruitment process is completed if we have moved forward to the next phase. The process includes two tests: one personality test and one cognitive test. The tests are tools to find the right talent for the right position, to enable equality, diversity, and a fair process.

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.