Data Engineer (Databricks, Python, Spark)

At Hays , we are partnering with a leading integral company in the financial services and investment management sector to find an experienced Data Engineer to join a strategic data transformation project.

This is an exciting opportunity to work with international teams, modern cloud technologies, and large-scale financial datasets, helping build and enhance a key data platform that supports critical investment operations and analytics.

Design, develop, and maintain scalable data pipelines using Databricks.
Build Big Data solutions with Spark, PySpark, and cloud technologies.
Collaborate with global investment and technology teams to deliver data-driven solutions.
Support business stakeholders with data insights and reporting.
3+ years of Data Engineering experience including 2+ years designing and building Databricks data pipelines is required.
~2+ years of hands-on Python/Pyspark/SparkSQL and/or Scala experience
~2+ years of experience with Big Data pipelines or DAG Tools (Data Factory, Airflow, dbt, or similar)




~2+ years of Spark experience (especially Databricks Spark and Delta Lake)
~2+ years of hands-on experience implementing Big Data solutions in a cloud ecosystem, including Data/Delta Lakes
~ Azure cloud is highly preferred, however will consider AWS, GCP or other cloud platform experience in lieu.
~ 2+ years of SQL experience , specifically to write complex, highly optimized queries across large volumes of data is highly desired
~ Experience working in a controlled environment with Github and CI/CD release pipelines is highly desired
~ Experience with financial data providers such as Bloomberg in an asset/investment management firm or other financial service company is a plus.
~ Experience with conceptual, logical and/or physical database designs is a plus
~ Must be comfortable speaking English
~ Hybrid and flexible working model: only 1 day per week on-site at the Barcelona office (Via Augusta)
Opportunity to join

📌 Senior Engineer, Data Engineering (Valladolid)
🏢 Hays
📍 Valladolid