Senior Data Engineer/Architect (AWS)
Senior data engineer/architect at Chaos Gears, a European AWS consulting partner. Day to day you design and build data lakehouse/warehouse platforms on AWS for clients in regulated industries, owning delivery end to end ('we build it, we run it'). Core stack: AWS data services, Apache Iceberg, dbt, Airflow, Kafka, Python and Terraform.
- Compensation
- PLN 23K–PLN 29K / mo
- Location
- 100% remote
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Contract
- Experience
- 5+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 5+ years in data engineering with production-grade delivery
- Hands-on experience with dbt and at least one modern orchestration tool (Airflow preferred)
- Solid Python skills and experience building and operating data pipelines
- Familiarity with data lake / data lakehouse concepts (Apache Iceberg) and batch/streaming architectures
- Experience with at least one modern warehouse or query engine
- Comfort with Infrastructure as Code (Terraform or similar)
- High agency: organize your own work to deliver goals without step-by-step direction
- Fluency in both English (C1) and Polish (C1), written and spoken
Nice to have
- Current experience in the healthcare industry (HL7 FHIR, OMOP CDM), or willingness to grow in this specialization
Full description
Ready to reshape a data platform from the ground up? Join Us!
As a leading AWS Partner in Europe, we support organizations at every stage of their cloud journey. Our strength comes from deep experience in cloud-native architectures. By joining our Data & AI team, you'll design and build scalable data platforms on AWS, work hands-on with the modern data stack, and directly shape how businesses in regulated industries process, store, and make sense of their data.
You won't be locked into one project. Our projects range from greenfield builds to re-architecting existing platforms, from small two-week engagements to multi-year deliveries, across several industries. Some weeks you design a data lake from scratch, other weeks you migrate an orchestration layer or tune a warehouse. What stays constant is ownership: we work in a "we build it, we run it" model, so every engineer deploys their own solutions to production without handing off to anyone else.
The stack you'll work with
We pick tools per project, but this is the technology you'll typically touch:
- Data Warehouse / Data Lakehouse architectures on AWS alongside streaming and batch pipelines,
- Apache Iceberg as the open table format,
- Data Warehouses and query engines: DuckDB, Amazon Redshift, Amazon Athena, Amazon S3 Tables, Snowflake, ClickHouse, and other AWS-native data services,
- Airflow (AWS MWAA) and AWS Step Functions for orchestration,
- Apache Kafka and Amazon Kinesis for streaming, Debezium for CDC,
- dltHub for ingestion, dbt with Cosmos (ELT) or Apache Spark (ETL) for data transformations,
- Amazon ECS for running application workloads,
- OpenMetadata for metadata and data lineage,
- Terraform for infrastructure as code.
Your 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 when needed,
- Ensure data quality, observability, and lineage across the platform,
- Deploy your own solutions to production, no handoffs, full ownership,
- Collaborate with a small engineering team and contribute to technical decisions.