Hybrid Data Engineer for Gaming Analytics & Pipelines

Gaming1; Lisboa; Hybrid; EUR 45,000 - 65,000; Full time

Benefits offered by this job

Hybrid work model

Career development opportunities

Job summary

Gaming1 is seeking a Data Engineer to implement data quality tests, collaborate with domain data teams, and optimize data pipelines and contracts. You will document steps and share knowledge to ensure long-term sustainability, while investigating failed loads and coordinating fixes with stakeholders.

You will work in a hybrid, international environment, contributing to ambitious global projects and benefiting from continuous learning and internal mobility.

Qualifications

• 3+ years building cloud data pipelines with solid SQL, Python/PySpark, and Airflow (or similar scheduler).
• Experience implementing idempotent or merge-based ingestion patterns.
• Familiarity with automated testing frameworks for data (Great Expectations, Soda tests).
• Strong soft skills: mentoring, documentation mindset, willingness to “leave the campsite cleaner,” and a strong collaborative approach.

Responsibilities

• Implement data quality tests that reflect business rules and technical validation tests.
• Collaborate with the domain cluster’s Data Engineer(s) or stakeholders, document steps and conduct knowledge-transfer sessions.
• Optimize jobs and implement data contracts; identify schema or pipeline improvements for maintainability.
• Investigate failed loads or QA breaches quickly and coordinate fixes with stakeholders.

Skills

SQL

Python/PySpark

Mentoring

Documentation mindset

Tools

Airflow

Great Expectations

Soda tests

Job description

Gaming1 is seeking a Data Engineer to implement data quality tests, collaborate with domain data teams, and optimize data pipelines and contracts. You will document steps and share knowledge to ensure long-term sustainability, while investigating failed loads and coordinating fixes with stakeholders.

You will work in a hybrid, international environment, contributing to ambitious global projects and benefiting from continuous learning and internal mobility.