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# Data Engineer

- **Company:** Remotestar
- **Location:** Spain
- **Contract:** Permanent contract
- **Skills:** Query Performance, 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, NoSQL, Operational Databases, Cloud Services, Standard Sql, SQL Databases, User-Centered Design, Management of Software Versions, Parquet, Apache Spark, Data Lakes, Git Flow, Kubernetes, Data Pipelines
- **Published:** July 31, 2026
- **Apply:** https://www.jobleads.com/es/job/eafb26f845d96358b65d30a5cf824dd39

## About the Role

* 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

## 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)
- [Parquet, Delta, Iceberg & Ducklake - An introduction for developers](https://www.wearedevelopers.com/videos/100075-parquet-delta-iceberg-ducklake-an-introduction-for-developers)
- [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt)
- [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis)
- [Implementing continuous delivery in a data processing pipeline](https://www.wearedevelopers.com/videos/73-implementing-continuous-delivery-in-a-data-processing-pipeline)
- [Tomorrow's cloud data platforms - fully managed database-as-a-service (DBaaS)](https://www.wearedevelopers.com/videos/254-tomorrow-s-cloud-data-platforms-fully-managed-database-as-a-service-dbaas)

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