Must have

• Python

• SQL

• dbt

• Cloud

• Polish

• English

Requirements description

• 2+ years of experience as a Data Engineer, focusing on data pipelines and transformations.
• 1+ year of hands-on Python experience, especially using Pandas.
• 2+ years working with SQL and relational databases.
• Experience with dbt for transformations and Git/GitLab CI/CD for versioning and automation.
• Understanding of data modeling, ETL concepts, and data warehouse design.
• Familiarity with cloud platforms (GCP, AWS, Azure – GCP preferred but optional).
• Experience with different types of storage systems: filesystem, relational, MPP, NoSQL.
• Good knowledge of DevOps tools (e.g., Docker, Jenkins, Terraform) and Unix/Linux systems.

Nice to Have

• Experience with real-time streaming, data quality frameworks, and distributed systems.
• Exposure to open-source or proprietary tools like Airflow, Glue, or Dataflow.
• Very good understanding of Gitflow development process.

Your responsibilities

1. Design, build, and maintain robust data pipelines and ETL/ELT processes.
2. Work with Python (especially Pandas) and SQL to transform and process structured and unstructured data.
3. Use dbt and GitLab for data transformations and version control / CI/CD workflows.
4. Collaborate with analysts, data scientists, and engineers to deliver clean, high-quality data.
5. Ensure best practices in data architecture, documentation, and metadata management.
6. Work with Snowflake for scalable data warehousing (warehouses, schemas, access control).

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