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Addepar is a global data and AI platform serving 1,500+ firms managing nearly $10 trillion in assets. The company unifies portfolio, market, and client data to deliver AI-powered insights within investment workflows, integrating with 650+ software and data partners.
You will lead Addepar's precompute platform — the foundational layer that pre-calculates financial analytics and transparently integrates precomputed and real-time results. This platform operates on terabyte-scale datasets using vector-oriented programming and distributed systems to achieve sub-second query performance for enterprise-scale wealth management firms.
Key responsibilities:
- 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 strategic data architecture and workflows
- Drive integration with core compute infrastructure, growing the share of query traffic served through the precompute layer
- Build 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 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
You will lead a global, distributed engineering team through production system transformation, with hands-on technical involvement in vector-based data processing and large-scale, high-concurrency systems.
REQUIREMENTS:
- 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
- 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 — build and act on usage analytics and cost/performance/accuracy tradeoffs
- 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
- Right to work in the United Kingdom from day one; visa sponsorship is not available
