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Senior Data Engineer

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Summary

Senior Data Engineer on an initial 12-month hybrid contract in Warsaw, building and operating large-scale production ETL/ELT pipelines in Python. Core stack includes Python data tooling (pandas, Polars, PySpark), orchestrators (Airflow, Dagster, dbt), a public cloud (AWS/Azure/GCP), and cloud data platforms like Snowflake or Databricks.

Our client currently seeks a Senior Data Engineer to join their dynamic team on an initial 12 month contract. This role is Hybrid and based in Warsaw.

EXPERIENCE

  • - Shipping production Python, not just scripts or notebooks.
  • - Building and operating ETL/ELT pipelines at scale.
  • - Python data tooling: pandas, Polars, PyArrow, DuckDB, or PySpark.
  • - Schema enforcement and validation: Pydantic or similar.
  • - Workflow orchestration in code: Airflow, Dagster, Prefect, dbt, or Temporal.
  • - Testing and quality tooling: pytest, pyright, ty, pyrefly, ruff or black.
  • - Dependency and environment management: uv, Poetry, pip-tools, or conda.
  • - At least one public cloud (AWS, Azure, or GCP) and its Python SDK, with familiarity with the others.
  • - Cloud data platforms: Snowflake, Databricks, BigQuery, or Redshift.
  • - Relational and non-relational databases, including schema design.

Preferred

  • - Python web/API frameworks (FastAPI, Flask).
  • - Async Python, multiprocessing, or other concurrency patterns.
  • - Streaming: Kafka, Kinesis, or Spark Structured Streaming.
  • - Infrastructure as code and automation (Terraform, GitHub Actions).
  • - Docker and Kubernetes.
  • - A second language: Go, Rust, Scala, or TypeScript.
  • - Generative AI, machine learning, or data science tooling.

Skills

See also

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