Descripción del trabajo
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 releaseDesign, implement, and operate large-scale ETL/ELT pipelines and workflow orchestration for clean, accurate, versioned dataDefine data modeling, partitioning, schema evolution, and versioning conventions to keep datasets queryable and reproducibleEstablish authoritative data catalogs with schemas, metadata, lineage, sensitivity labels, and access policiesValidate released datasets against sources for completeness, correctness, and performance with objective acceptance criteriaCollaborate with ML/AI engineers to make data products consumable by analytics, APIs,



and AI/agent workflowsLead knowledge transfer with clients and cross-functional teams; mentor and review designs/code to raise engineering standardsStay 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 field4+ years of professional data engineering experience with ownership of production data platforms or pipelinesExpert Python programming and strong SQLData 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 KubernetesSolid data governance knowledge (catalogs, metadata, lineage, access control, versioning)Git-based workflows, CI/CD, and infrastructure-as-code experienceExcellent problem-solving, communication, and collaboration skills (English)
Requisitos principales
Indefinite contractEqual pay guaranteedVariable performance bonusSigning bonusWork visa sponsorshipRelocation package (if applicable)
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📌 Senior Data Engineer (Principado de Asturias)
🏢 Multiverse Computing
📍 Principado de Asturias