Senior Data Product Engineer, Upvest

• If you care about reliability, scalability, and lowering the barrier to working with data - this is your role
• Strong experience building and operating event-driven data pipelines, ideally with Kafka or similar streaming infrastructure
• Experience with Python, Go or another systems-level language for building data infrastructure
• Solid SQL skills for data transformation, modelling, and staging layer development
• Familiarity with infrastructure-as-code tooling such as Terraform for managing cloud resources
• Experience working with cloud providers such as GCP, AWS, or Azure (we run primarily on GCP)
• Experience with schema design and data modelling principles - able to advise teams across the organization
• Experience setting up data observability and monitoring (Datadog, Grafana, Prometheus, etc.)
• A product and consulting mindset - able to understand the needs of engineers, analysts, and business users and translate them into platform solutions
• Strong communication skills and ability to promote data literacy across the organization

Desirable

• Upvest's data platform powers near real-time financial analytics about operations across trading, payments, risk, and compliance. We're building the next generation of our data infrastructure - an Iceberg-backed Lakehouse and CDC-powered pipelines that give engineers, analysts, and business users a single, reliable place to work with data at scale
• You'll own our Kafka consumer and CDC pipelines, help architect and deliver the Lakehouse foundation, and act as a trusted consultant for data integration, modelling, and schema design across the organization
• Own and improve the Kafka consumer pipeline that captures, transforms, and warehouses event data
• Design and build CDC-based pipelines to capture and replicate changes from source systems into the data platform
• Design, build and maintain foundational data serving layers that scale and serve the use cases of engineering and analytics alike
• Act as a data consultant across the organization - advising on data integration, modelling, and schema design for teams building on or contributing to the platform
• Deliver self-service data solutions that enable engineers, analysts, and business users to work with the data platform independently
• Drive data observability: set up tests, metrics, and alerting for pipeline health and data quality using observability tooling such as Datadog
• Work closely with product engineering teams to ensure reliable, timely data availability
• Champion data culture - share knowledge, establish best practices, and help teams understand and trust their data