Descripción del trabajo

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Our client is a fast-growing deep-tech company founded in 2019 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 general enterprises across several critical industries, including finance, energy, manufacturing, telecom, and industrial sectors.

Required Qualifications

Bachelors or masters 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

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

Nice to have

Experience with scientific or geospatial data formats and tooling (e.g., Zarr, NetCDF, GRIB2, xarray, H3 spatial indexing)

Experience preparing and serving data for LLM, RAG, or agent-based applications





Previous experience in consulting or client-facing delivery teams

Perks and Benefits

Indefinite contract.

Equal pay guaranteed.

Variable performance bonus.

Signing 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.

Language classes and discounted lunch options.

A high-performance, collaborative environment, operating at pace on cutting-edge technologies.

Career plan. xugodme Opportunity to learn and teach.

Responsibilities

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 teams 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

📌 Senior Data Engineer (España)
🏢 Sabia Personal
📍 España