Data Platform Engineer

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.

TL;DR - We are looking for analytics engineers to own the semantic and modeling layer of our warehouse by transforming raw data into well-defined, trustworthy datasets and metrics. You are obsessed with analytical consistency, designing impactful metrics, and building strong foundations for self-service analytics. Why Lovable? Lovable lets anyone and everyone build software with plain English. From solopreneurs to Fortune 100 teams, millions of people use Lovable to transform raw ideas into real products - fast. We are at the forefront of a foundational shift in software creation, which means you have an unprecedented opportunity to change the way the digital world works. Over 2 million people in 200+ countries already use Lovable to launch businesses, automate work, and bring their ideas to life. And we’re just getting started. We’re a small, talent-dense team building a generation-defining company from Stockholm. We value extreme ownership, high velocity and low-ego collaboration. We seek out people who care deeply, ship fast, and are eager to make a dent in the world. What we are looking for: Expertise with SQL, dbt, SQLMesh or similar tools (data modeling, testing, macros, docs) Experience with data warehousing concepts, cloud warehouses (Snowflake, BigQuery, Redshift, Databricks) and BI tools (Looker, Tableau, Power BI, Hex, Metabase, etc) Understanding of dimensional modeling, data contracts, and metrics/semantical layers Familiarity with modern ELT and orchestration workflows (Airflow, Dagster, Prefect, etc) Strong business acumen and ability to translate domain logic into scalable data structures What you will do: Build and maintain data models, following modular, tested, and version-controlled practices Partner with domain teams to understand business logic and codify it into reusable models and metrics Define and document key metrics and data contracts across domains Collaborate with Data Platform Engineers to optimize query performance and warehouse cost Automate and maintain data documentation, lineage, and governance standards Develop guidelines for analytics development, data modeling and structure conventions Our tech stack We're building with tools that both humans and AI love: Frontend: React Backend: Golang and Rust Cloud: Cloudflare, GCP, AWS, Many LLM providers DevOps & Tooling: Github Actions, Grafana, OTEL, infrastructure-as-code (Terraform) And always on the lookout for what's next! How we hire Fill in a short form then jump on an intro call with recruiter. Complete the general programming exercise. Show us how you approach problems during several technical interviews. Tell us about your most impressive project. About your application Please submit your application in English - it’s our company language so you’ll be speaking lots of it if you join We treat all candidates equally - if you’re interested please apply through our careers portal