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Data Engineer Mid-Level (m/f/d)
Job description
Your Tasks:
Lakehouse & Data Engineering (approx. 50%):
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Conception, setup, and tuning of performant pipelines based on Databricks.
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Data modeling with dbt and orchestration of robust DAGs via Apache Airflow.
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Governance & Performance:
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Establishment of automated data quality checks, data lineage, and cluster optimization.
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Analytics & Data Apps (approx. 25%):
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Building a semantic metrics layer and self-service BI in Lightdash.
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Development of interactive analysis tools and data apps in Python (Streamlit).
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Data Science & ML (approx. 25%):
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Exploratory analyses, prototyping, and training of ML models (e.g., forecasts, anomalies).
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MLOps & Business Integration:
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Experiment tracking on Databricks and delivery of results to business units.
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Your Profile:
Professional Experience:
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At least 2–4 years of practical experience in Data Engineering, Analytics Engineering, or a comparable role.
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Core Engineering Stack:
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Solid practical experience with Databricks (Delta Lake, Unity Catalog), dbt, and Apache Airflow.
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BI & Data Apps:
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Experience with Lightdash (or interest in code-based BI) and with Streamlit.
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Code & Database Languages:
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Excellent SQL (performance tuning, complex joins) and very good Python (pandas, PySpark, scikit-learn).
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Methodology & Best Practices:
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Proficient use of Git / CI/CD and modern modeling concepts (Star Schema).
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Mindset & Languages:
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Pragmatic hands-on mentality, strong communication skills, and very good German & English.
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- Sustainable travel with our e-car leasing
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Company information
- Company
- Octopus Energy Group
- Location
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Berlin (DE)
Germany - Posted
- 1 day ago
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