Senior Data Engineer

Sabia Personal; Valencia; Presencial; EUR 60.000 - 90.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Contrato indefinido

Igualdad de salario garantizada

Bono de rendimiento

Bono de firma

VISA de trabajo y relocation

Seguro de salud privado

Budget educativo según política

Modalidad híbrida en sus oficinas de (

Descripción de la vacante

Sabia Personal está buscando un ingeniero de datos senior para diseñar y entregar plataformas de datos avanzadas (lakehouse, catálogo y gobernanza). Serás responsable de pipelines ETL/ELT a gran escala y la orquestación de flujos, asegurando datos limpios y versionados para consumo por analítica y APIs.

Colaborarás con equipos de ML e ingeniería para adaptar datos a requerimientos y trabajarás directamente con clientes para definir requisitos, mentores y mejoras de estándares.

Formación

• Bachiller o Maestría en CS/ingeniería de software o campo relacionado.
• 4+ años de experiencia en data engineering y gestión de pipelines.
• Dominio de Python y SQL.
• Modelado de datos, ETL y gestión de bases SQL/NoSQL.
• Experiencia con lakehouse y formatos columnar (Parquet, Iceberg, Delta).
• Experiencia con Spark y orchestrators (Airflow/Argo).
• Experiencia en plataformas en la nube (Azure/AWS/GCP) y Kubernetes.
• Conocimientos de gobernanza de datos, catálogos y control de acceso.
• Inglés para discusiones técnicas con clientes.

Responsabilidades

• Diseñar y entregar arquitecturas de plataformas de datos (lakehouse, catálogo, gobernanza).
• Desarrollar y operar pipelines ETL/ELT a gran escala y orquestación de flujos.
• Definir modelado, particionamiento, evolución de esquemas y versionado.
• Mantener catálogos de datos, metadatos, linaje y políticas de acceso.
• Validar datasets liberados respecto a fuentes: completas, correctas y con buen rendimiento.
• Colaborar con ML/ingenieros para hacer datos consumibles por analítica, APIs y flujos AI.
• Trabajar con clientes y equipos para definir requisitos y documentar arquitecturas.
• Mentorizar a otros data engineers y elevar estándares de ingeniería.
• Mantenerse al día con tendencias y promover su adopción cuando aporta valor.

Conocimientos

Python

SQL

Data modelling

ETL/ELT

Lakehouse

Spark

Airflow

Kubernetes

Cloud platforms

Git CI/CD IaC

English communication

Educación

Bachelor's or Master's degree in CS/Software Eng

Herramientas

Parquet

Apache Iceberg

Delta Lake

Argo Workflows

Zarr

NetCDF

xarray

Descripción del empleo

Descripción del trabajo

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 global 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. 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