Senior Engineer, Data Engineering

Our client is a fast-growing deep-tech company founded in ** and recognized by CB Insights as one of the 100 most promising AI companies globally.They are the largest quantum software company in the EU, with 250+ employees worldwide and growing, delivering advanced solutions trusted by leading global enterprises across several critical industries, including finance, energy, manufacturing, telecom, and industrial sectors.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 · 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 · able to lead technical discussions with clients and stakeholders in English Experience with scientific or geospatial data formats and tooling (e.G., Experience preparing and serving data for LLM, RAG, or agent-based applications · Indefinite contract.Variable performance bonus.They offer work visa sponsorship (If applicable) and relocation package (if applicable).Private health insurance.Eligibility for educational budget according to internal policy.Hybrid opportunity in their offices located in San Sebastian.Flexible working hours.A high-performance, collaborative environment, operating at pace on cutting-edge technologies.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 · 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

They are the largest quantum software company in the EU, with 250+ employees worldwide and growing, delivering advanced solutions trusted by leading global enterprises across several critical industries, including finance, energy, manufacturing, telecom, and industrial sectors. 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 · 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 · able to lead technical discussions with clients and stakeholders in English Experience with scientific or geospatial data formats and tooling (e.G., Experience preparing and serving data for LLM, RAG, or agent-based applications · Indefinite contract.

They offer work visa sponsorship (If applicable) and relocation package (if applicable). Private health insurance. Eligibility for educational budget according to internal policy. Hybrid opportunity in their offices located in San Sebastian. Flexible working hours. A high-performance, collaborative environment, operating at pace on cutting-edge technologies. 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 · 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

Our client is a fast-growing deep-tech company founded in ** and recognized by CB Insights as one of the 100 most promising AI companies globally.