Data Engineer (Airflow / Snowflake)
Description
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:
Design, build, and maintain Apache Airflow DAGs in Python that load data into the Data Lake (S3) and Snowflake.
Build pipelines that ingest data from APIs, databases, and files.
Model and transform data with dbt.
Tune SQL queries and Snowflake performance and cost.
Set up monitoring, alerting, and error handling for pipelines.
Protect data quality through testing and validation, and keep documentation current.
Key Requirements:
3+ years of experience as a Data Engineer.
Apache Airflow: strong knowledge of operators, sensors, hooks, TaskFlow API, XCom, pools, backfills, and idempotent DAG design.
Python: strong skills, with clean, testable code and pytest.
SQL: advanced level, including window functions, CTEs, and query optimization.
Snowflake: hands-on experience with warehouses, stages, external volumes, COPY INTO.
dbt: models, tests, macros, snapshots, and incremental models.
AWS S3: Data Lake organization, partitioning, file formats (Parquet, JSON, CSV), and IAM policies.
Git and CI/CD experience.
English at B2 level or higher.
Nice to Have
Docker and Kubernetes.
Open table formats: Apache Iceberg or Delta Lake.
Data quality and observability tools such as Great Expectations or Soda.
Dimensional modeling (Kimball).