Remote Data Engineer: Airflow & Snowflake Pipelines

emagine; Polska; Remote; PLN 182,000 - 259,000; Full time

Job summary

emagine is seeking a skilled Data Engineer specializing in Apache Airflow and Snowflake. The ideal candidate will design, build, and maintain data pipelines with a focus on performance optimization and data quality.

Proficiency in Python, SQL, and cloud storage solutions is essential. Responsibilities include creating Airflow DAGs loading data into Snowflake and S3, building pipelines from APIs/databases/files, modeling with dbt, and tuning SQL for cost efficiency.

Qualifications

• 3+ years of experience as a Data Engineer.
• Strong Apache Airflow knowledge: operators, sensors, TaskFlow, XCom, pools, backfills, idempotent DAGs.
• Strong Python skills with clean, testable code and pytest.
• Advanced SQL knowledge including window functions, CTEs, and optimization.
• Snowflake experience with warehouses, stages, external volumes, COPY INTO.
• dbt models, tests, macros, snapshots, and incremental models.
• AWS S3 data lake organization, partitioning, formats (Parquet, JSON, CSV), and IAM.
• Git and CI/CD experience.
• English at B2 level or higher.
• Nice to have: Docker, Kubernetes, Open table formats (Iceberg/Delta Lake), data quality/observability tools like Great Expectations or Soda, Dimensional modeling (Kimball).

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.

Skills

Data engineering

Airflow

Python

SQL

English

Tools

Snowflake

dbt

AWS S3

Git

CI/CD

Job description

emagine is seeking a skilled Data Engineer specializing in Apache Airflow and Snowflake. The ideal candidate will design, build, and maintain data pipelines with a focus on performance optimization and data quality.

Proficiency in Python, SQL, and cloud storage solutions is essential. Responsibilities include creating Airflow DAGs loading data into Snowflake and S3, building pipelines from APIs/databases/files, modeling with dbt, and tuning SQL for cost efficiency.