Data Engineer

PeopleForce; Polska; Hybrid; PLN 180,000 - 250,000; Full time

Benefits offered by this job

Remote-first flexibility

Global team

Wellbeing and paid leave

Job summary

Weltrade is seeking a Data Engineer to own the data warehouse and ELT pipelines in BigQuery, collaborating with analysts to deliver trusted datasets. You will design scalable data models, ensure data quality, and optimize performance for analytics, marketing attribution, and product reporting.

The role requires strong SQL and Python, hands-on BigQuery, dbt, and Airflow experience, plus knowledge of data modeling and ELT design. Remote-first, global team, and ownership culture.

Qualifications

• Strong SQL with joins, window functions and delta detection.
• Hands-on BigQuery or cloud DWH experience.
• Production dbt experience: models, tests, macros.
• Orchestration with Airflow or equivalent.
• Data modeling expertise (Kimball, Inmon, Data Vault, Anchor).
• ELT/ETL design with incremental loads and backfills.
• Experience with data quality, testing and pipeline monitoring.

Responsibilities

• Design, build, and maintain data models and the DWH layering in BigQuery.
• Develop and orchestrate ELT pipelines with dbt and Airflow.
• Model data and select appropriate modelling approach per use case.
• Implement data quality checks, tests, and monitoring; fix failures.
• Manage schema evolution from upstream sources.
• Optimize warehouse performance and cost with partitioning and tuning.
• Document data lineage and collaborate with analysts on metrics truth.

Skills

SQL

Python

BigQuery

dbt

Airflow

Data modeling

ELT/ETL design

Data quality monitoring

Tools

dbt

Airflow

BigQuery

Job 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.
• Implement data quality checks, tests, and monitoring; investigate and fix pipeline failures.
• Manage schema evolution and breaking changes from upstream sources.
• Optimize warehouse performance and cost (partitioning, clustering, query tuning).
• Document data lineage and models; collaborate with analysts and stakeholders on the source of truth for metrics.

What We Offer

• Remote-First Flexibility: We operate fully remotely and offer a global and cross-functional environment.
• Ownership & Impact: A chance to own ideas and make a measurable impact on organizational growth and client experience.
• Wellbeing: Well-balanced leave allowance (paid vacation, sick leave, public holidays, etc.) and a supportive culture that values every employee.

Recruitment Process

Application Review → HR Interview → Technical Interview → Final Interview → Offer