Your Tasks

Coordination & Organization (approx. 50%):

• Leading the team and coordinating data-related activities across teams.
• Maintaining and updating documentation on data pipelines, workflows, and system architectures.
• Planning, tracking, and reporting on data engineering tasks and deliverables.
• Ensuring compliance with internal standards, processes, and data governance policies.
• Ensuring communication flow between technical and non-technical stakeholders.
• Driving continuous improvement of operational processes and tools.

Technical Implementation (approx. 50%):

• Developing and operating performant, reliable, and distributed applications based on functional programming.
• Working with Spark in DataBricks, ensuring resilience and elasticity in large deployments.
• Building and optimizing data-intensive workflows with Apache Spark or similar frameworks.
• Applying solid knowledge of runtime environments, execution contexts, and pure functional design.
• Co-designing architectural solutions for distributed and parallel data transformation.
• Developing efficient, maintainable code in Python.

Your Profile

• Strong practical experience in functional programming (ETL pipelines, actor-model systems like Akka/Apache Pekko, categorical systems, or map-reduce frameworks).
• Hands-on experience with Apache Spark (central) or comparable technologies (Apache Flink, Cats/Cats Effect, Hadoop, Kafka Streams).
• Solid understanding of runtime systems, execution contexts, and pure functions.
• Deep understanding of compiled, JIT, and interpreted execution models.
• Proficiency in Python and Scala/Java, C/C++ or Rust.
• Experience in project work including planning, coordination, and tracking technical tasks.
• Experience collaborating in cross-functional teams with a focus on synchronization and knowledge sharing.