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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Enpal GmbH - **Location:** Berlin, Germany - **Contract:** Permanent contract - **Skills:** Airflow, Data Analysis, Databases, Data Governance, Data Infrastructure, Programming Tools, Python (Programming Language), Role-Based Access Control, Data Processing, Snowflake, Containerization, Kubernetes, Software Coding, Terraform - **Published:** July 4, 2026 - **Apply:** https://de.indeed.com/viewjob?jk=74e72f255a7ddfff ## About the Role * Strong software engineering fundamentals: Python, testing, reusable libraries, and a platform-as-product mindset. * Deep, hands-on dbt experience at scale (not just authoring models, but operating the platform around them). * Solid Snowflake knowledge: RBAC, performance, and warehouse management. * Experience with orchestration (Airflow) and containerized workloads (Kubernetes/AKS). * Comfort with IaC (Terraform) and GitOps (ArgoCD). * Familiarity with modern ingestion frameworks (dlt or similar). * Excellent communication and stakeholder empathy; you enjoy enabling other engineers and can navigate ambiguity in a cross-domain mesh., * Experience building internal developer platforms or paved-road tooling. * Knowledge of data contracts and federated data governance. * GDPR/DSGVO-aware data handling experience. * Exposure to Snowflake Iceberg/REST catalogs or dbt Fusion. Are you interested even if you don't meet all the requirements? Apply anyway! We look forward to discovering your potential-regardless of whether your experience meets every single requirement. ## Description Our central Data Platform team builds the paved road that domain Analytics Engineering and BI teams build on top of within our data mesh. As a Data Platform Engineer, your customers are developers, not dashboards: you own the tooling, abstractions, and guardrails that let 55+ AE/BI engineers embedded across domains ship dbt models safely and fast across a ~2,500-model monorepo. You'll work at the intersection of dbt, Snowflake, orchestration, and infrastructure-as-code, and you'll spend as much time unblocking and enabling others as you do writing code., * Own and evolve our dbt platform: macros, packages, project structure, selective/state-aware runs, and CI gating across a large monorepo. * Build self-service scaffolding and developer tooling so domain teams can create models, sources, and tests without touching platform internals. * Manage infrastructure as code with Terraform and ArgoCD (GitOps), keeping environments reproducible and reviewable. * Enforce federated governance: data contracts, RBAC via Snowflake database roles, and domain ownership boundaries. * Support data privacy and compliance requirements, including metadata-driven PII handling. * Build observability and testing into the platform so failures are caught before they reach domain teams. * Partner with AE/BI leads to gather requirements, review designs, document patterns, and continuously lower the barrier to entry. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [The Biggest German Tech Companies](https://www.wearedevelopers.com/magazine/424-the-biggest-german-tech-companies) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Where To Find Software Engineering Jobs](https://www.wearedevelopers.com/magazine/396-where-to-find-software-engineering-jobs) - [The 12 Best Jobs for Software Engineers](https://www.wearedevelopers.com/magazine/401-the-12-best-jobs-for-software-engineers)