I’m expanding our data engineering team and need an experienced engineer who can take ownership of end-to-end, real-time data pipelines built in Scala, Spark, Java and Python. You’ll partner closely with our data scientists and analysts, translate their requirements into performant streaming solutions, and keep those pipelines humming around the clock. You’ll be working with Apache Kafka, Apache Flink and Databricks on a daily basis, so deep production experience with these platforms is essential. Solid SQL skills, a track record of writing comprehensive unit and integration tests, and familiarity with cloud-native services and data governance practices will let you hit the ground running. Key outcomes I’m looking for: • Design and deploy new streaming jobs that meet latency and throughput SLAs • Refactor and optimise existing Spark/Scala code for efficiency and maintainability • Implement automated data quality checks, monitoring and alerting • Troubleshoot pipeline failures quickly and document permanent fixes • Collaborate with the analytics team to expose clean, well-modelled data sets Success will be measured by the reliability of the pipelines, the clarity of your documentation, and the performance gains you deliver. If you hold a degree in Computer Science or Engineering, have hands-on expertise with real-time processing in Kafka, Flink and Databricks, and enjoy solving complex data problems in a highly collaborative environment, I’d love to hear how you can help us scale.