Data Engineer Greece - Mid Level

Design, build, and maintain data pipelines that serve models, data, and AI workflows to internal and client-facing applications.

Work across database types — relational, vector, and graph — to model and store data appropriately for each access pattern, in partnership with data scientists.

Build and maintain dbt models — writing transformation logic, tests, and documentation that ensure data quality and traceability.

Operate what you build : instrument pipelines with logging, metrics, and tracing, and help diagnose and resolve production data issues.

Write clean, tested, production-quality code and contribute to CI/CD pipelines and infrastructure-as-code.

Participate in code reviews, design discussions, and retrospectives.

2–4 years of professional data engineering experience, with work deployed to production.

Strong proficiency in at least one general-purpose language (e.g., Python, Scala, or Java) and comfort working across a codebase.

Solid fundamentals in designing and building data pipelines (ETL/ELT), with experience in Apache Spark for large-scale data processing.

Experience with cloud platforms (GCP/AWS), containers (Docker), and CI/CD.

Strong software engineering practices — Git, testing, code review, CI/CD.

Clear communication — you can explain technical choices and trade-offs to both technical and non-technical colleagues.

Experience integrating ML/LLM systems into production applications (model serving, RAG, agents).

Familiarity with infrastructure-as-code (Terraform), orchestration, and observability tooling.

Experience with event-driven or streaming architectures (e.g., Pub/Sub, Kafka).

Exposure to security, IAM, and data governance in cloud environments.

Background in marketing technology, ad tech, or large-scale data products.