Industry: IT
Rate: up to 160 pln/h net + VAT, B2B
Location: 100% remote
About role:
We are seeking a skilled and experienced Data Engineer specializing in Apache Airflow and Snowflake. The ideal candidate will have a strong background in designing and maintaining data pipelines, with a focus on performance optimization and data quality. Essential skills include proficiency in Python and SQL, alongside hands-on experience with data modeling and cloud data storage solutions.
Main Responsibilities:
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Design, build, and maintain Apache Airflow DAGs in Python that load data into the Data Lake (S3) and Snowflake.
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Build pipelines that ingest data from APIs, databases, and files.
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Model and transform data with dbt.
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Tune SQL queries and Snowflake performance and cost.
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Set up monitoring, alerting, and error handling for pipelines.
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Protect data quality through testing and validation, and keep documentation current.
Key Requirements:
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3+ years of experience as a Data Engineer.
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Apache Airflow: strong knowledge of operators, sensors, hooks, TaskFlow API, XCom, pools, backfills, and idempotent DAG design.
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Python: strong skills, with clean, testable code and pytest.
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SQL: advanced level, including window functions, CTEs, and query optimization.
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Snowflake: hands-on experience with warehouses, stages, external volumes, COPY INTO.
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dbt: models, tests, macros, snapshots, and incremental models.
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AWS S3: Data Lake organization, partitioning, file formats (Parquet, JSON, CSV), and IAM policies.
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Git and CI/CD experience.
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English at B2 level or higher.
Nice to Have
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Docker and Kubernetes.
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Open table formats: Apache Iceberg or Delta Lake.
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Data quality and observability tools such as Great Expectations or Soda.
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Dimensional modeling (Kimball).
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