Data Engineer (Apache Spark) - (Financial Services)

Your new company

Working for a renowned financial services organisation

Your new role

We are seeking a Data Engineer to support the replacement of a legacy ETL tool with a modern Apache Spark based data platform. This is a hands‑on engineering role focused on building and supporting Spark jobs, with an emphasis on performance, reliability, and scalability.

The role is focused on building nonperformance Apache Spark jobs, with a strong emphasis on performance optimisation. It is primarily Java‑based, with Python strongly encouraged; experience across Java, Python, and Scala is ideal, with Java and Python being the preferred combination.

The role sits within a small Agile delivery team of four engineers (two onshore and two in Shenzhen), working closely with a Senior Data Engineer. You will be responsible for development work, sprint delivery, demos, documentation, and stakeholder engagement. This position suits a mid‑level engineer with strong Spark development experience rather than design, infrastructure, or management responsibilities.

What you'll need to succeed

Strong hands‑on experience with Apache Spark - Writing and tuning Spark jobs /PySpark development experience
Strong Java or Java Spring boot development background
Experience with programming in Python or Scala
Exposure to Big Data technologies and distributed data processing
Working with containerised environments using Kubernetes/ Airflow.
Agile ways of working (Scrum, sprints, demos)
Comfortable working in a distributed team
Financial services or professional services experience required.
What you'll get in return
Flexible working options available.

What you need to do now
If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now.

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