Build and maintain data pipelines that power analytics, ML workloads, and product-facing applications - from internal databases, SaaS sources, and streaming systems through to the teams and services that consume them.
Evolve our data platform alongside cloud platform engineers, using infrastructure-as-code (Terraform) and Kubernetes-based deployments (Argo) to keep the platform scalable, reliable, and self-serve.
Design and implement scalable data infrastructure that accommodates our growing data volume and complexity.
Develop data services and APIs that expose trusted data to product applications, bridging analytical and operational systems.
Own data quality and observability, putting monitoring, testing, and alerting in place so issues are caught early and trust in the data stays high.
Partner with AI engineers, data scientists, analysts, and product teams to understand their data needs and design the right solutions – not just the quickest ones.
Uphold strong data privacy, security, and compliance practices in everything you build, particularly where data flows into product-facing contexts.
Create and maintain comprehensive documentation of data flows, models, and systems for knowledge sharing.
Ensure all data systems adhere to security best practices and compliance requirements.

3+ years building and shipping production grade data systems
Strong SQL skills
Proficiency in Python or another object-oriented language (Java, Scala etc.)
Familiarity with cloud-native infrastructure - ideally some exposure to Terraform, Kubernetes, or similar IaC and container orchestration tools
Experience designing data APIs or services that expose data to applications, or a strong interest in working across the analytical/operational boundary
A thoughtful approach to data quality, privacy, and security
Strong collaboration skills and comfort working across teams with different priorities — engineers, data scientists, AI engineers, product
A pragmatic, curious mindset - you enjoy keeping up with the field and know when to reach for a new tool versus when to stick with what works
Hands on experience with data pipeline tools (Airflow, dbt)
Strong ability to optimise for performance and reliability
Commitment to continuously improving product quality, security, and performance through rigorous testing and code reviews
Meticulous approach to creating and maintaining architecture and systems documentation
Exceptional analytical skills to troubleshoot complex data issues and implement effective solutions
Capability to ship medium features independently while contributing to the team's overall objectives

Prolific is hiring a Senior Data Engineer