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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** Multiverse Computing - **Location:** San Sebastián, Spain - **Contract:** Permanent contract - **Skills:** Query Performance, Geographic Information Systems, Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Apache HTTP Server, Microsoft Azure, Computer Programming, Continuous Integration, Information Engineering, Data Governance, Extract Transform Load (ETL), Distributed Computing Environment, Interoperability, Python (Programming Language), Machine Learning, Metadata, NetCDF, NoSQL, Operational Databases, Cloud Services, Standard Sql, Software Engineering, SQL Databases, User-Centered Design, Management of Software Versions, Parquet, Large Language Models, Apache Spark, Data Lakes, Git Flow, Kubernetes, Information Technology, Data Pipelines - **Published:** July 23, 2026 - **Apply:** https://es.indeed.com/viewjob?jk=14b1a0f4fcf76e71 ## About the Role * Bachelors or master's degree in computer science, software engineering, or a related field * 4+ 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 Nice to have: * Experience with scientific or geospatial data formats and tooling (e.g., Zarr, NetCDF, GRIB2, xarray, H3 spatial indexing) * Experience preparing and serving data for LLM, RAG, or agent-based applications * Previous experience in consulting or client-facing delivery teams ## Description * 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 transfer and internal ownership * Mentor and support other data engineers, reviewing designs and code and raising the team's engineering standards * Stay up to date with emerging trends in data engineering - open table formats, data catalogs, orchestration - and drive their adoption where they add value ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [NoSQL Data Modeling for Front-end Developers](https://www.wearedevelopers.com/videos/297-nosql-data-modeling-for-front-end-developers) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries)