Bachelors or master's degree in computer science, software engineering, or a related field
5+ years of professional experience in data engineering, including ownership of production data platforms or pipelines
Expert programming skills in Python and strong command of SQL
Expertise in data modeling, ETL development, and database management, with both SQL and NoSQL databases
Hands-on experience with lakehouse architectures and columnar / open table formats (e.G., Parquet, Apache Iceberg, Delta Lake)
Experience with distributed data processing frameworks such as Spark, and with workflow orchestrators such as Airflow or Argo Workflows
Strong experience with cloud data platforms (Azure, AWS, or GCP), including object storage, containers, and Kubernetes
Solid grounding in data governance: catalogs, metadata, lineage, access control, and dataset versioning
Comfortable with Git-based workflows, CI/CD, and infrastructure-as-code working models
Excellent problem-solving, communication, and collaboration skills;
able to lead technical discussions with clients and stakeholders in English




Responsibilities Own the end-to-end design and delivery of data platform architectures — lakehouse, data catalog, and governance — from initial scoping through production release
Design, implement, and operate large-scale ETL/ELT pipelines and workflow orchestration to ensure data is clean, accurate, versioned, and accessible
Define data modeling, partitioning, schema evolution, and versioning conventions so datasets remain queryable, interoperable, and reproducible at scale
Establish and maintain authoritative data catalogs, including schemas, metadata, lineage, sensitivity labels, and access policies
Validate released datasets against their sources for completeness, correctness, schema consistency, and query performance, defining objective acceptance criteria
Work closely with Machine Learning and AI Engineers to make data products directly consumable by analytics, APIs, and AI/agent workflows
Collaborate with clients and cross-functional teams to scope requirements, lead technical sessions, and document architectures for knowledge

📌 Senior Data Engineer (Madrid)
🏢 RemoteStar
📍 Madrid