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Lead Data Engineer
to help design, build, and scale a modern enterprise data platform on AWS. This is a hands‑on role for someone who enjoys solving complex data problems, building high‑performance pipelines, and shaping how data is used across an organization. You’ll work on large‑scale data systems that integrate multiple enterprise sources to deliver trusted, production‑grade data products that power analytics, reporting, and decision‑making. What You’ll Do
Build and optimize scalable data pipelines and platforms on AWS (S3, Glue, Redshift, EMR/Spark, Athena, Lambda). Lead technical design and delivery of major data initiatives from concept through production. Partner closely with architects, analytics teams, and business stakeholders to turn requirements into reliable data assets. Implement modern ELT/ETL frameworks with orchestration, CI/CD, testing, and monitoring. Drive data quality, performance, security, and cost optimization across the platform. Establish engineering best practices through design and code reviews and technical standards. What We’re Looking For
8+ years of experience in data engineering, including experience leading enterprise‑scale solutions. Deep expertise in AWS data services and cloud‑native architectures. Strong skills in Python, PySpark/Scala, and advanced SQL. Proven experience building data lakes, lakehouse platforms, and cloud data warehouses. Hands‑on experience with orchestration tools (Airflow, Step Functions) and modern DevOps practices. Strong communicator who can bridge technical and business teams. Nice to Have
Experience with Apache Iceberg and modern table formats. Background in data governance, enterprise integrations, or ML‑enabled data platforms.
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Sprachkenntnisse
- English
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