Mid Level Data Engineer

This is a fully remote position, open to applicants in Greece.

📋 Description

• Develop and manage pipelines and data models that transform raw data into clean, reliable, and thoroughly documented datasets.

• Create robust ETL/ELT pipelines that ingest, transform, and deliver large datasets throughout the marketing intelligence stack.

• Design well-documented, tested, and version-controlled dbt data models that empower downstream AI and BI.

• Structure data in the warehouse/lakehouse and relational databases, selecting appropriate structures for each access pattern.

• Implement orchestration, monitoring, data quality checks, and data lineage.

• Design, construct, and maintain production data pipelines for analytics, BI, and AI workflows.

• Build SQL-based transformations and models into documented, tested datasets.

• Design and manage data warehouses/lakehouses and relational databases, such as PostgreSQL.

• Contribute to pipeline infrastructure, orchestration, CI/CD, and infrastructure-as-code for the data platform.

• Collaborate closely with data scientists and software engineers.

• Own pipelines from start to finish.

• Share expertise and knowledge with the team.

⛳️ Requirements

• Over 4 years of experience in building and managing production data pipelines and data models.

• Proficient in SQL and data modeling, including SQL-based transformations (dbt or similar).

• Strong background with a data warehouse or lakehouse.

• Solid Python skills; familiarity with Scala or Java is a plus.

• Good software engineering practices, including version control, testing, code reviews, and CI/CD.

• Experience with pipeline orchestration tools like Airflow, Dagster, or similar.

• Hands-on experience with cloud platforms such as GCP or AWS.

• Capability to draft concise design documents useful for product managers and engineers.

• Nice to have: experience with distributed data processing at scale, such as Apache Spark.

• Nice to have: knowledge of containers, including Docker, and infrastructure-as-code, such as Terraform.

• Nice to have: familiarity with vector databases like Pinecone, Weaviate, or pgvector, or graph databases such as Neo4j or Neptune.

• Nice to have: exposure to ML/LLM-powered data systems, including RAG, embeddings, and feature/serving pipelines.

• Nice to have: experience with event-driven or streaming data technologies, including Pub/Sub, Kafka, and real-time pipelines.

🏝️ Benefits

• Healthcare coverage.

• Remote working options — whether in a café, at home, or on the beach.

• Truly flexible working hours.

• Generous leave in accordance with Greek Labour Law.

• Opportunity to work on impactful projects focused on meaningful social and environmental change.

• People-oriented culture that prioritizes wellbeing.

• Transparent and open organizational culture.

• Opportunities for professional development.

• Autonomy and freedom in your work.

• An inclusive and warm workplace culture.