Data Engineer

Remotestar

Spain

11 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience required

5 years minimum

Working hours

Regular working hours

Languages

English

Job source

www.jobleads.com

Tech stack

Query Performance Application Programming Interfaces (APIs) Artificial Intelligence Airflow Amazon Web Services Data Analysis Apache HTTP Server Microsoft Azure Computer Programming Continuous Integration Information Engineering Data Governance

+19 more

Extract Transform Load (ETL) Distributed Computing Environment Interoperability Python (Programming Language) Machine Learning Metadata NoSQL Operational Databases Cloud Services Standard Sql SQL Databases User-Centered Design Management of Software Versions Parquet Apache Spark Data Lakes Git Flow Kubernetes Data Pipelines

Job description

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 team’s 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

Requirements

Bachelors or master’s degree in computer science, software engineering, or a related field
5+ 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