Addepar - Sr. Engineering Manager, Precompute
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 • 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 • Our Values • Act Like an Owner - Think and operate with intention, purpose and care. Own outcomes. • Act Like an Owner - • Build Together - Collaborate to unlock the best solutions. Deliver lasting value. • Build Together - • Champion Our Clients - Exceed client expectations. Our clients’ success is our success. • Champion Our Clients - • Drive Innovation - Be bold and unconstrained in problem solving. Transform the industry. • Drive Innovation - • Embrace Learning - Engage our community to broaden our perspective. Bring a growth mindset. • Embrace Learning -
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 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
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