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Gypsy Collective

DWH Engineer

🇵🇱 Remote, Poland Remote IT Full time Posted May 27, 2026
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Location Remote, Poland
Workplace Remote
Employment Full time
Category IT
IT Category Data Engineer
Language English
Posted May 27, 2026
Last verified June 7, 2026
JobGrid context

Role summary by JobGrid

DWH Engineer at Gypsy Collective: Remote, Poland; Full time; IT; Data Engineer. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.

  • Location and workplace: Remote, Poland
  • Role classification: IT, Data Engineer, Full time
  • Source freshness: checked by JobGrid on 2026-06-07.
  • Application path: candidates continue to the employer application page with non-personal referral tags.

Gypsy Collective is looking for a DWH Engineer to join our team and help build scalable, reliable, and high-performance data warehouse solutions that support analytics and business decision-making. We are looking for an experienced and proactive engineer who can work across the full data lifecycle - from ingestion and modeling to optimization, monitoring, and automation - while collaborating closely with analysts, developers, and business stakeholders.

📅 Your daily adventures include:

  • Designing, building, and maintaining scalable Data Warehouse architectures aligned with business needs;
  • Developing and optimizing ETL/ELT pipelines using Python, Airflow, and custom solutions;
  • Working with DWH/Data Lake technologies including PostgreSQL, Trino, and BigQuery;
  • Implementing incremental loads, CDC, backfills, and reprocessing strategies;
  • Optimizing query performance, data models, and pipeline execution;
  • Ensuring data quality through validation, automated testing, monitoring, and alerting;
  • Integrating new data sources (APIs, third-party systems, raw data) without disrupting existing pipelines;
  • Collaborating with analysts, engineers, BI teams, and business stakeholders to translate requirements into scalable data solutions;
  • Reviewing code, mentoring engineers, and contributing to data engineering standards and best practices.