Gypsy Collective
Middle DWH Engineer
Lokalizacja
Zdalnie, Ukraina
Tryb pracy
Zdalnie
Forma zatrudnienia
Pełny etat
Poziom doświadczenia
Średni poziom
Kategoria
IT
Kategoria IT
Inżynier danych
Język
English
Opublikowano
2 czerwca 2026
Ostatnio sprawdzono
3 czerwca 2026
Kontekst JobGrid
Podsumowanie roli od JobGrid
Middle DWH Engineer at Gypsy Collective is a full-time mid-level IT / Data Engineer role based remotely in Ukraine. JobGrid normalizes the role facts from the source payload, keeps the employer description separate, and routes candidates to the original public application page with non-personal referral parameters.
- Role title: Middle DWH Engineer at Gypsy Collective, Remote, Ukraine.
- Structured classification: IT category, Data Engineer subcategory, Mid seniority, Full time.
- Source freshness is shown from the payload: posted 2026-06-02 and last checked 2026-06-03.
- No salary is listed in the payload, so salary context is unavailable here.
We are looking for a Middle DWH Engineer to design, build, and maintain scalable data warehouse solutions that support analytics and business decision-making. You will work across the full data lifecycle - from data ingestion and transformation to orchestration and optimization - while collaborating with analysts, engineers, and business stakeholders.
📅 Your adventures include:
- design, develop, and maintain DWH and Data Lake solutions aligned with business requirements;
- build, optimize, and support ETL/ELT pipelines using Python, SQL, Airflow, and related technologies;
- integrate and maintain data flows from APIs, databases, SaaS platforms, and third-party systems;
- work with PostgreSQL, Trino, and cloud-based analytical platforms to support reporting and analytics needs;
- implement and support incremental loading, CDC processes, backfills, and reprocessing workflows;
- monitor, troubleshoot, and improve data pipelines to ensure reliability, stability, and timely delivery of data;
- implement data quality checks, validation rules, and automated monitoring processes;
- optimize SQL queries, data models, and pipeline performance;
- collaborate with analysts, BI developers, engineers, and business stakeholders to deliver scalable data solutions;
- participate in code reviews and contribute to engineering standards and best practices.