Experteer Overview
In this role you will design and deliver data platform architectures to support analytics, ML, and AI workflows at a fast-growing quantum software company. You will own end-to-end data pipelines, catalogs, and governance, ensuring clean, versioned data accessible for teams and clients. You’ll work with cross-functional teams to translate requirements into scalable lakehouse solutions and drive data stewardship and reproducibility. This position offers exposure to cutting-edge tech and a mission-driven, inclusive culture.

Compensaciones / Incentivos
• Own end-to-end design and delivery of data platform architectures (lakehouse, data catalog, governance) from scoping to production release
• Design, implement, and operate large-scale ETL/ELT pipelines and workflow orchestration for clean, accurate, versioned data
• Define data modeling, partitioning, schema evolution, and versioning conventions to keep datasets queryable and reproducible
• Establish authoritative data catalogs with schemas, metadata, lineage, sensitivity labels, and access policies
• Validate released datasets against sources for completeness, correctness, and performance with objective acceptance criteria
• Collaborate with ML/AI engineers to make data products consumable by analytics, APIs, and AI/agent workflows




• Lead knowledge transfer with clients and cross-functional teams; mentor and review designs/code to raise engineering standards
• Stay up to date with data engineering trends (open table formats, data catalogs, orchestration) and drive adoption where valuable

Responsabilidades
• Bachelors or master's degree in computer science, software engineering, or a related field
• 4+ years of professional data engineering experience with ownership of production data platforms or pipelines
• Expert Python programming and strong SQL
• Data modeling, ETL development, and database management (SQL and NoSQL)
• Hands-on experience with lakehouse architectures and columnar/open table formats (Parquet, Apache Iceberg, Delta Lake)
• Experience with distributed processing (Spark) and workflow orchestration (Airflow, Argo Workflows)
• Strong cloud data platform experience (Azure, AWS, or GCP) including object storage, containers, and Kubernetes
• Solid data governance knowledge (catalogs, metadata, lineage, access control, versioning)
• Git-based workflows, CI/CD, and infrastructure-as-code experience
• Excellent problem-solving, communication, and collaboration skills (English)

Requisitos principales
• Indefinite contract
• Equal pay guaranteed
• Variable performance bonus
• Signing bonus
• Work visa sponsorship
• Relocation package (if applicable)

📌 Senior Data Engineer (San Sebastián)
🏢 Multiverse Computing
📍 San Sebastián