Data Engineer (Spark/ Kubernetes) (Financial Services)

Description

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. You shall be running Spark workloads in containerised environments using Kubernetes and programming skillset in Python/ Scala or Java is also a required skillset.

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 experience working in with containerised environments using Kubernetes.

Experience with programming in Python or Scala

Exposure to Big Data technologies and distributed data processing

Have some experience using Java/ Java Spring boot for development.

Experienced in an Ops way of working, not pure development only - you know how to deploy solutions.

Experience with OpenShift would be highly desirable!

Experience working in an Agile way of working (Scrum, sprints, demos)

Financial services or professional services experience required.

What you'll get in return

Flexible working options available. xjnqpsq

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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Ad ID: 5418188452