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Data Engineer at GT, Remote (Europe)

Metris is transitioning from a functional MVP to a scalable, structured data platform, and is looking for a Data Engineer to support a 2–3 month migration effort.

• Your focus will be to move existing Python/SQL ETL jobs into a new framework and rebuild core pipelines—particularly those handling inverter and performance data.
• You’ll work closely with the Senior Data Engineer, who provides architectural direction and reviews, while you take ownership of day-to-day execution.
• The environment is fast-moving, high-trust, and pragmatic, with an emphasis on clean implementation, speed, and autonomy. The tech stack includes Python, SQL, cloud-native tools, and an internal Airflow-like orchestrator (Airflow experience is helpful but not required).

Responsibilities

• Migrate existing Python/SQL ETL jobs into the new data platform.
• Rebuild and refactor pipeline logic following established architectural patterns.
• Work with inverter, sensor, and performance data pipelines to ensure accurate ingestion.
• Deliver high-quality implementations across multiple independent, parallelizable tasks.
• Produce clean, consistent, production-ready code.
• Collaborate with the Senior Data Engineer for reviews and technical alignment.
• Troubleshoot issues and validate data correctness after migration.
• Document changes clearly and maintain logical clarity across pipelines.
• Communicate progress proactively and manage your work independently.

Essential knowledge, skills & experience:

• Strong proficiency in Python for data engineering tasks.
• Hands-on experience with ETL pipelines, data ingestion, or similar workflow-driven systems.
• Ability to refactor, migrate, and clean up existing codebases.
• Solid knowledge of SQL for data querying and transformations.
• Experience delivering work in fast-paced, execution-focused environments.
• Comfortable working with minimal supervision and owning tasks end-to-end.
• Ability to ensure accuracy, reliability, and consistency across data pipelines.

Nice-to-have

• Experience with Airflow or similar orchestration systems.
• Exposure to cloud-native data environments or data platform migrations.
• Familiarity with IoT, sensor data, or time-series data processing.
• Experience working in early-stage or high-growth tech environments.

Interview Steps

• GT interview with Recruiter
• Technical interview
• Offer