Descripción del trabajo
Compruebe que cumple con los requisitos de habilidades para este puesto, así como con la experiencia asociada, y luego envíe su CV a continuación.
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 xqbhyrx 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)
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📌 Senior Data Engineer (Oviedo)
🏢 Multiverse Computing
📍 Oviedo