Sr. Engineering Manager, Precompute

Overview

You will own and scale Addepars precompute layer, delivering faster analytics for large wealth-management clients. You’ll shape a platform-wide performance layer that handles incremental and real-time results with sub-second latency. Your work spans vectorised processing, distributed data architectures, and cross-region scalability. You’ll partner with product and engineering leadership to meet aggressive performance KPIs and drive governance in data workflows. This role offers impact at scale within a global, data-driven fintech platform.

Responsibilities

• Own the precompute platform roadmap with product and engineering leadership, targeting high-performance processing and low-latency queries for enterprise clients
• Architect and implement solutions to reduce complexity through strategic data architecture and streamlined workflows
• Increase query traffic served by the precompute layer by integrating with core compute infrastructure
• Build repeatable, scalable architecture for multi-region deployment
• Advance vectorisation of calculations, moving from row-based to columnar processing for throughput gains
• Enhance team efficiency by coordinating with operational partners
• Embed Data Publisher responsibilities into precompute workflows and achieve data health indicators

Key requirements

• Extensive software engineering or data platform experience with performance engineering at scale
• Hands-on leadership in vector-based data processing
• Experience leading global, distributed engineering teams through production transformations
• Strong cloud data infrastructure background: AWS, Databricks, Kubernetes
• Ability to influence across teams and drive architectural decisions
• Data-driven prioritisation mindset with analytics on usage, cost, performance, and accuracy
• Data Governance experience and integration into engineering workflows
• cross-team technical influence
• data-driven decision making
• collaborative problem-solving
• vector-based data processing
• performance engineering for large-scale, high-concurrency systems
• distributed systems

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