Data Engineer Mid-Level (m/w/d)

Lakehouse & Data Engineering (approx. 50%):

• Conception, construction and tuning of high-performance pipelines based on Databricks.

• Data modeling with dbt and orchestration of robust DAGs via Apache Airflow.

• Governance & Performance:

  • Establishment of automated data quality checks, data lineage and cluster optimization.

  • Analytics & Data Apps (approx. 25%):

    • Building a semantic metrics layer and self-service BI in Lightdash.

    • Development of interactive analysis tools and data apps in Python (Streamlit).

    • Data Science & ML (approx. 25%):

      • Exploratory analysis, prototyping and training of ML models (e.g. predictions, anomalies).

      • MLOps & Business Integration:

        • Experiment tracking on Databricks and making the results available to departments.

Work experience:

• At least 2-4 years of experience in data engineering, analytics engineering or a comparable role.

• Core Engineering Stack:

  • In-depth practice with Databricks (Delta Lake, Unity Catalog), dbt and Apache Airflow.

  • BI & Data Apps:

    • Experience with

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