Senior Data Engineer/Architect (AWS)

Chaos Gears; United States; Remote; USD 66,000 - 83,000; Full time

Benefits offered by this job

B2B contract 23 000-29 000 PLN net

Medical care package

Multisport card co-financing

Training budget

Language learning platform access

Flexible working hours & remote work

Company events

Continuous learning and growth

Job summary

Chaos Gears is building a data platform on AWS, delivering scalable data lakehouse architectures and ELT pipelines using dbt, Airflow, and modern warehouses. You will own end-to-end data solutions, from ingestion to observability, in a hands-on role with real ownership.

Join a small engineering team, design orchestration, migrate between layers, and push production-ready code. Fluency in English and Polish is required; remote-friendly with flexible hours and continuous learning opportunities.

Qualifications

• 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/lakehouse concepts (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: autonomous, goal-driven, can organize own work to deliver.
• Fluency in English and Polish, written and spoken (C1/C1).

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.

Skills

Data engineering

dbt

Airflow

Python

Data Lakehouse

Terraform

English

Polish

Batch processing

Observability

Tools

Apache Iceberg

DuckDB

Amazon Redshift

Amazon Athena

Snowflake

Kafka

Kinesis

dbt

OpenMetadata

Terraform

Airflow MWAA

Job 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 lineageacross the platform,
• Deploy your own solutions to production, no handoffs, full ownership,
• Collaborate with a small engineering team and contribute to technical decisions.

Requirements:

• 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: you get a goal, not a step‑by‑step list, and you organize your own work to deliver it. You don't wait to be told what to do next,
• Fluency in both English (C1) and Polish (C1), written and spoken.

Nice to have:

• Current experience in the healthcare industry will be a big plus, or a willingness to grow in this specialization. We build platforms for hospitals and research institutions, based on the HL7 FHIR and OMOP CDM data models. If you are curious to explore it and deep dive into it, that is enough to start.

What we offer:

• B2B contract 23 000-29 000 PLN net,
• Continuous learning and growth – we invest in your development through internal training, knowledge‑sharing sessions, and hands‑on learning from real projects. We also support growth beyond the organization by actively engaging in the AWS Community, including conference talks and industry events.
• Training budget– dedicated funds to support certifications, courses, and professional development aligned with your career goals.
• Medical care package – comprehensive private healthcare to help you stay healthy and focused.
• Multisport card co‑financing – because staying active matters, both in and outside of work.
• Language learning platform access– improve your language skills at your own pace, whenever it suits you.
• Flexible working hours & remote work– work when and where you’re most productive.
• Company events– time for integration and some fun.

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