Data Engineer: AWS Lakehouse & ELT Pipelines

Chaos Gears

United States

Hybrid

USD 43,000 - 68,000

Full time

3 days ago
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Benefits offered by this job

B2B contract 15 000-24 000 PLN net
Continuous learning & growth
Training budget
Medical care package
Multisport card co-financing
Language learning platform access
Flexible working hours & remote work
Company events

Job summary

Chaos Gears is seeking a data engineer to design and build scalable data platforms on AWS, owning ELT pipelines and production deployments. You'll work with a modern data stack including dbt, Airflow, Iceberg, and multiple data services.

This role emphasizes ownership across the data platform lifecycle. The team is small, focused on quality and observability, with opportunities to influence architecture and data governance.

Qualifications

  • 3+ years in data engineering (production-grade delivery).
  • Solid Python skills and data pipelines experience.
  • Fluency in English (C1) and Polish (C1).
  • Hands-on with dbt and orchestration tools (Airflow preferred).
  • Comfort with data lake/lakehouse concepts (Iceberg).
  • Experience with at least one modern warehouse/query engine.
  • Infrastructure as Code (Terraform).
  • High agency: own goals and deliver.

Responsibilities

  • Design, implement and maintain Data Lakehouse and Warehouse architectures on AWS.
  • Build and maintain ELT pipelines using dbt, dltHub, and Airflow.
  • Design orchestration and migrate between orchestration layers as needed.
  • Ensure data quality, observability, and lineage across the platform.
  • Deploy own solutions to production with full ownership.

Job description

Chaos Gears is seeking a data engineer to design and build scalable data platforms on AWS, owning ELT pipelines and production deployments. You'll work with a modern data stack including dbt, Airflow, Iceberg, and multiple data services.

This role emphasizes ownership across the data platform lifecycle. The team is small, focused on quality and observability, with opportunities to influence architecture and data governance.

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