Data Engineer
Data Engineer at Weltrade (FX/online trading) who owns the company data warehouse and ELT pipelines powering analytics, marketing attribution, and product reporting — designing scalable data models in BigQuery with dbt and Airflow and ensuring data quality with analysts and stakeholders.
- Compensation
- Not disclosed
- Location
- Poland
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 19+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Strong SQL (joins, window functions, delta/change detection)
- Solid Python skills
- Hands-on experience with BigQuery (or comparable cloud DWH)
- Production experience with dbt: models, tests, macros
- Orchestration experience with Airflow (or equivalent)
- Data modeling expertise: Kimball / Inmon / Data Vault / Anchor modeling, layer boundaries and trade-offs
- ELT/ETL design: incremental extraction, backfills, schema evolution
- Experience with data quality, testing, and pipeline monitoring
Nice to have
- Integration with ad-platform APIs (Google Ads, Facebook/Meta) and marketing attribution data
- Experience building AI/LLM data pipelines
- Experience building agents / agentic workflows
- Product analytics exposure (AppsFlyer, GTM, server-to-server, enhanced conversions)
- CI/CD for data pipelines
Full description
Become a part of Weltrade, a reliable international company with over 19 years of experience in the FX and online trading market.
Join our Global Team! Work From Anywhere! Grow With Us!
About Weltrade
Weltrade is a leading international Fintech company with over two decades of stability and trust in the global FX and online trading industry. Established in 2006, we operate as a truly global, remote-first organization, bringing together high-performing professionals across multiple time zones.
We focus on building scalable trading infrastructure and high-impact commercial ecosystems that drive sustainable client acquisition worldwide. At Weltrade, we value ownership, autonomy, and measurable impact.
About your Role
As a Data Engineer, you will own the company's data warehouse and the pipelines that power analytics, marketing attribution, and product reporting. You'll design and maintain scalable data models and ELT pipelines in BigQuery using dbt and Airflow, transforming raw data into reliable, business-ready datasets. Working closely with analysts and stakeholders, you'll ensure data quality, optimize performance, and help build a trusted foundation for data-driven decision-making.
You Have
- Strong SQL (joins, window functions, delta/change detection) and solid Python.
- Hands-on experience with BigQuery (or a comparable cloud DWH).
- Production experience with dbt: models, tests, macros.
- Orchestration experience with Airflow (or equivalent).
- Data modeling expertise: Kimball / Inmon / Data Vault / Anchor modeling, and reasoning about layer boundaries and trade-offs.
- ELT/ETL design: incremental extraction, backfills, schema evolution.
- Experience with data quality, testing, and pipeline monitoring.
Good to have
- Integration with ad-platform APIs / advertising cabinets (Google Ads, Facebook/Meta) and marketing attribution data.
- Experience building AI/LLM data pipelines.
- Experience building agents / agentic workflows.
- Product analytics exposure (AppsFlyer, GTM, server-to-server, enhanced conversions).
- CI/CD for data pipelines.
Responsibilities
- Design, build, and maintain data models and the DWH layering (raw → staging → core → mart) in BigQuery.
- Develop and orchestrate ELT pipelines with dbt and Airflow — incremental loads, idempotent/re-runnable jobs, backfills.
- Model data using established methodologies (Kimball, Inmon, Data Vault, Anchor modeling) and choose the right approach per use case.