Senior Lead Software Engineer – Data & Analytics

Overview

In this role you will design and deliver a firmwide metrics and analytics platform that makes engineering performance visible, driving decisions at scale. You will own end-to-end delivery—from data pipelines to dashboards—working with engineering leaders across the firm. This position combines data, product, and platform work to shape how the organization understands and improves its engineering capability. You will contribute to a culture of secure, scalable software and responsible AI-enabled development, delivering measurable impact.

Responsibilities

• Design and implement modern web dashboards and end-to-end workflows to transform engineering data into insights for teams and leaders
• Build and operate reliable data pipelines to ingest, transform, validate, and publish metric datasets, integrating with platforms like Databricks
• Develop secure, scalable backend services and REST APIs to enable metric consumption and power the UI
• Define metric logic, conduct exploratory and trend analyses, and translate findings into dashboard narratives for engineering decisions
• Collaborate with engineering teams and stakeholders to align on performance benchmarks and a coherent metrics strategy
• Implement CI/CD, automated testing, secure coding standards, and code reviews for production-grade software
• Deploy and operate services on cloud and container platforms ensuring reliability and scalability
• Leverage enterprise-authorized AI coding assist tools to improve code quality and productivity while validating outputs via peer review and testing
• Apply SDLC toolchain knowledge to improve automation value through AI-assisted development and tooling

Key requirements

• Formal training or certification on software engineering concepts and advanced applied experience
• Full-stack engineering capability with end-to-end dashboards and web experiences
• Experience with SQL databases and analytical data stores at scale, data warehouses, and query optimization
• CI/CD, automated testing, and code review practices
• Analytical ability to develop and validate metrics and translate results into visual narratives
• Strong communication and stakeholder partnership skills
• Understanding of responsible AI use, data sensitivity, secure handling, and security resiliency
• Hands-on experience with enterprise-authorized AI-assisted development tools and ability to validate AI outputs

• effective communication
• stakeholder partnership
• analytical thinking
• React
• TypeScript
• REST API design

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