Data Engineer — Hybrid/Remote, Growth & Impact

Gaming1; Luik; Hybrid; EUR 70,000 - 95,000; Full time

Benefits offered by this job

Hybrid working model

Remote up to 50%

Job summary

Gaming1 is seeking a Data Engineer to help build reliable, scalable data products that support decision-making across the group. You will design, build and operate data pipelines and models used by analysts and business teams.

Join a data mesh environment with a focus on accessible, well-documented data; you will own end-to-end data flows from ingestion to reporting-ready tables, working in SQL, PySpark and with Power BI.

Qualifications

• Strong SQL skills and the ability to write and optimise complex queries.
• Experience with PySpark (or Python) in a data-engineering context.
• Solid data-modelling knowledge, including Kimball-style star schemas.
• Around 3–6 years of hands‑on data-engineering experience, with the autonomy to own work from source to reporting-ready data.
• A collaborative mindset, clear communication skills and comfort working in the gaming industry.
• Professional English.

Responsibilities

• Build data products: design and develop pipelines and models in SQL and PySpark, from ingestion to analytics-ready tables.
• Model data: create clear dimensional models that analysts and Power BI reports can use directly.
• Own quality: implement tests based on business rules, investigate failed loads and improve reliability.
• Improve what exists: tune jobs, evolve schemas and pipelines, reduce compute costs, and leave the codebase better than you found it.
• Share knowledge: document your work in the project’s Git repository so it is easy to understand, maintain and reuse.

Skills

SQL

PySpark

Data modelling

English

Team collaboration

Tools

Power BI

Airflow

dbt

Great Expectations

Job description

Gaming1 is seeking a Data Engineer to help build reliable, scalable data products that support decision-making across the group. You will design, build and operate data pipelines and models used by analysts and business teams.

Join a data mesh environment with a focus on accessible, well-documented data; you will own end-to-end data flows from ingestion to reporting-ready tables, working in SQL, PySpark and with Power BI.