Lead Data Product Engineer

We're looking for a Lead Data Product Engineer to build the foundation that makes our data and AI products possible. You'll design and maintain the centralized datasets, pipelines, and integrations that connect modern AI-enabled and AI-first systems with the existing tools our business runs on. Partnering with engineering, analytics, and business stakeholders, you'll identify gaps, establish trusted sources of truth, and simplify how data moves across the organization. You'll also be bringing engineering rigor to data and AI workflows through best practices in versioning, testing, observability, and deployment.

KEY RESPONSIBLITIES:

• Identify gaps in our current data ecosystem and chart a pragmatic path forward
• Establish and maintain centralized, well-defined datasets as sources of truth
• Map and document end-to-end data models, flows, and dependencies across systems, tools, and products
• Build data pipelines using Python, SQL, and orchestration tools (e.g., Prefect)
• Design and implement integrations between AI systems and existing systems
• Support production AI workflows, ensuring reliability, scalability, and observability
• Partner with stakeholders to standardize how data moves across the organization
• Implement guardrails for data quality, consistency, and lineage
• Introduce best practices around versioning, testing, deployment, and monitoring of production data and AI systems

SKILLS & QUALIFICAITONS

• 5+ years of engineering experience focused on data systems and pipelines
• Strong proficiency in Python, SQL, and orchestration tools
• Experience designing scalable data platforms and turning fragmented data into reliable, centralized datasets, with strong system design and data modeling skills
• Ability to design integrations across disparate systems (APIs, databases, third-party platforms) with a clear grasp of end-to-end data flows
• Familiarity with data quality, lineage, and observability practices for building resilient production systems
• Experience supporting AI/ML workflows in production
• Ability to take end-to-end ownership, and collaborate effectively with cross-functional stakeholders