Responsibilities

• Design, build and optimise scalable data pipelines handling high-volume, high-velocity financial data in real time
• Architect and maintain a modern data platform leveraging tools such as dbt, Apache Kafka, Spark and cloud-native services
• Implement and evolve data lakehouse patterns, working across structured and unstructured data at scale
• Drive adoption of DataOps practices, including pipeline testing, observability, lineage tracking and automated data quality frameworks
• Collaborate with data scientists, analysts and product teams to deliver data products that create tangible business value
• Champion engineering best practices across version control, CI/CD, documentation and peer review
• Contribute to platform and tooling decisions with a genuine seat at the table on architectural direction

Qualifications

• 4-5 years of experience in data engineering, with a track record of...