- Experience developing and supporting data solutions using Apache Spark and distributed processing frameworks.
- Experience developing applications in Scala or another object-oriented/JVM-based programming language.
- Strong understanding of software engineering principles including testing, code quality and maintainability.
- Experience with unit testing frameworks such as Xray or equivalent.
- Experience delivering solutions on Google Cloud Platform (GCP).
- Solid SQL Python skills for data analysis, troubleshooting, optimisation and data profiling.
- Experience working with BigQuery and large-scale analytical datasets.
- Familiarity with CI/CD and DevOps tooling including Maven, Git, Nexus, SonarQube, Harness and automated deployment pipelines.
- Experience using JIRA and Confluence to manage Agile delivery and technical documentation.
- Experience working within Agile teams using Scrum, sprint planning and iterative delivery practices.
- Strong communication and stakeholder management skills.
- Demonstrable ability to apply practical problem-solving techniques to real-world business and data challenges.
Nice to Have
- Experience with DataProc, Cloud Composer, GCS or other GCP data services.
- Experience within Financial Services, particularly Finance, Insurance, Regulatory Reporting or Risk data domains.
- Knowledge of modern data platform architectures and cloud migration programmes.
- Experience supporting production platforms and investigating data or operational issues.
- Exposure to DevOps, platform engineering or infrastructure-as-code practices.
- Previous experience with SAS, particularly in reporting, analytics or legacy platform support.
- Experience mentoring or supporting junior engineers and contributing to engineering communities of practice.