Data Engineer (Databricks, Python, Spark)
At
Hays
, we are partnering with a leading general 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.
What you will do
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.
Contribute to best practices, CI/CD processes, and continuous improvement initiatives.
Explore and leverage AI and LLM technologies to enhance platform capabilities.
What we are looking for
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.
Experience with
AI, LLMs, Databricks Genie
or similar tools is required
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 f
📌 Data Engineer (Madrid)
🏢 Hays
📍 Madrid