Company
RepRisk AG
Location
Berlin, Germany
Employment type
Full-time
Seniority
Senior
Primary category
Data Engineering
Posted date
9 Mar 2026
Valid through
8 May 2026
About You
Are you looking for an opportunity to build robust, scalable data infrastructure that powers meaningful, cutting-edge machine learning projects? Do you want to work at a company where your contributions have a real, measurable impact - and you're recognized and rewarded for it?
If you're passionate about data architecture, pipelines, and enabling ethical tech development, then this is the perfect role for you. We value autonomy, giving you the space to bring innovative engineering solutions to life in an inclusive, feedback-oriented environment. Your work will directly support NLP and machine learning initiatives that drive corporate responsibility through technology.
Your Responsibilities
As our new Senior Data Engineer, you will architect, build, and scale a modern data platform leveraging Databricks and lakehouse architecture principles. You will lead the design and delivery of enterprise-grade data infrastructure as part of our global Technology division. You will also:
Architect and implement end-to-end lakehouse solutions on Databricks, leveraging Delta Lake, Unity Catalog, and the Medallion architecture (Bronze/Silver/Gold)
Design, build, and maintain scalable, reliable ELT pipelines using Databricks workflows, Delta Live Tables, and Apache Spark
Develop and optimize high-throughput streaming and batch data pipelines using Spark Structured Streaming and Auto Loader
Drive data platform performance tuning, cost optimization, and cluster/compute governance across Databricks environments
Define and enforce data contracts, schemas, and governance standards through Unity Catalog and Delta Lake
Ensure data quality, observability, and lineage across the platform using tools such as Databricks Data Observability and Great Expectations
Collaborate cross-functionally with data scientists, analysts, and platform teams to deliver reliable, self-serve data products
Establish and champion internal data engineering best practices, standards, and reusable frameworks
Stay current with the Databricks ecosystem, lakehouse trends, and emerging data engineering patterns
Participate in code reviews to maintain high standards of quality, performance, and security
Engage actively in Agile/Scrum ceremonies, contributing architectural insights and technical direction to the team
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