Data Engineer – Mid Level
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Job Description
Data Engineer developing data pipelines and infrastructure at Satalia. Involved in large-scale data processing and collaboration with data scientists.
Responsibilities:
- 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.
Requirements:
- 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.
Benefits:
- healthcare
- Remote working - café, bedroom, beach - wherever works;
- Truly flexible working hours - school pick up, volunteering, gym;
- Generous Leave – inline with Greek Labour Law
- Impactful projects - focus on bringing meaningful social and environmental change;
- People oriented culture - wellbeing is a priority, as is being a nice person;
- Transparent and open culture - you will be heard;
- Development - focus on bringing the best out of each other;
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