Sr. Engineering Manager, Precompute

The Role

We are seeking a Precompute Platform Lead to own and scale Addepar's precompute layer — the platform that pre-calculates financial analytics and transparently integrates precomputed and real-time results, delivering step-change improvements in query latency and concurrency for enterprise-scale wealth management firms.

The team operates on terabyte-scale datasets, leveraging vector-oriented programming and distributed systems to enable sub-second performance. You will lead the evolution of this capability from targeted use cases to a platform-wide performance layer — solving hard problems in incremental computation, vectorised processing, and distributed data architecture as you scale.

Applicants must have, and maintain, the right to work in the United Kingdom from the first day of employment. Please note that visa sponsorship is not available for this role.

What You’ll Do

• Own the precompute platform roadmap in partnership with Product and engineering leadership, defining and meeting aggressive performance KPIs for daily processing, incremental processing, and query latency across enterprise clients
• Architect, implement, and maintain engineering solutions to solve sophisticated problems; reduce complexity through the adoption of strategic data architecture and workflows
• Drive integration with core compute infrastructure, growing the share of query traffic served through the precompute layer
• Continue global region support, building a repeatable architecture that scales across Addepar's multi-region deployment
• Drive deeper vectorisation of the calculation layer, moving compute-intensive factor math from row-by-row execution into the columnar engine for step-change throughput improvements
• Improve team efficiency by engaging with operational partners
• Drive Data Governance outcomes by integrating Data Publisher Responsibilities into precompute data creation workflows and achieving Data Health indicators for precompute artifacts

Who You Are 

• B.S., M.S., or Ph.D. in Mathematics, Statistics, or similar numerate field (or equivalent practical experience).
• Extensive background in software engineering or data platform roles, with significant experience in performance engineering under large scale and high-concurrency systems
• A hands-on engineering leader with demonstrated experience in vector-based data processing
• Experience leading global, distributed engineering teams through production system transformation
• Strong cloud data infrastructure background — AWS, Databricks, Kubernetes
• Cross-team technical influence — demonstrated ability to facilitate constructive discussions around complex technical and organisational issues and drive architectural decisions across team boundaries
• Data-driven prioritisation mindset — you build and act on usage analytics and cost/performance/accuracy tradeoffs, not just receive them
• Data Governance experience — familiarity with publisher responsibilities, data health indicators, and building governance into engineering workflows
• Finance or wealth management domain knowledge is a plus but not required
• A confident and positive outlook with low ego; high degree of ingenuity, resourcefulness, and problem-solving skills