Data platform engineer- Financial Services
Summary
Support and maintain enterprise Data Lake and Data Pipeline platforms for a well-established financial services organisation, monitoring workflows, resolving incidents, and assisting with cloud-to-on-premises migration. Core tech: Apache Spark, Apache Airflow, Kubernetes, and Docker.
- Support critical data platform transformation projects
- Exposure to Spark, Airflow, Kubernetes and Docker
About Our Client
Our client is a well-established organisation undergoing data platform transformation initiatives.
Job Description
- Support and maintain enterprise Data Lake and Data Pipeline platforms
- Monitor, troubleshoot, and optimise data processing workflows
- Ensure platform stability, availability, and operational performance
- Collaborate with data engineers and infrastructure teams on daily support activities
- Assist in cloud-to-on-premises platform migration and transformation projects
- Support deployment, configuration, and maintenance of data platform environments
- Participate in incident resolution and root cause analysis
- Contribute to platform enhancements and operational improvements
- Work with containerisation and orchestration technologies in distributed environments
The Successful Applicant
- 2-4 years of experience in Data Engineering, Platform Support, or Data Platform Operations
- Hands-on experience supporting Data Lakes and Data Pipelines
- Strong knowledge of Apache Spark and Apache Airflow
- Experience troubleshooting data processing and workflow issues
- Familiarity with cloud-based infrastructure and data platforms
- Understanding of production support and system monitoring practices
- Knowledge of Kubernetes (K8s) and Docker is highly preferred
- Exposure to cloud-to-on-premises migration or transformation projects is advantageous
- Strong analytical and problem-solving skills
- Ability to work effectively with cross-functional technical teams
What's on Offer
- Competitive salary package with stable career progression
- Opportunity to work on large-scale data platform transformation projects
- Exposure to modern data engineering and container technologies
