Staff Engineer

GEICO•Palo Alto, CA

2d•$115,000 - $230,000

About The Position

GEICO's Pulse team is looking for a Staff Software Engineer who is passionate about building data platforms that give engineering leaders a single source of truth for developer productivity. You will help drive our engineering transformation as we evolve from legacy technology to a living, API-driven insights platform — one that gives developers, managers, and executives meaningful, trustworthy data to make better decisions. This platform is transforming, and you will shape its next chapter. Our Staff Engineers work across levels to build new systems, improve existing ones, and solve critical problems with data and software. As a technical leader for the Developer Activity Metrics platform, you will define and execute a roadmap that turns raw ADO work item, PR, and AI usage data into clean, reliable, high-value metrics — powering dashboards, alerting, compliance reporting, and continuous improvement conversations across Developer Engineering. You will also help GEICO push the boundary of agentic development by making AI-assisted and agent-driven engineering work measurable, governable, and actionable. Quantifying the impact of these capabilities for technology teams, business leaders, and the broader software delivery organization will ensure that budget is invested in the right place. The ideal candidate combines deep software engineering expertise with strong experience in data pipeline engineering, metrics design, and platform thinking. You understand what it takes to keep ETL pipelines healthy, data quality high, and dashboards accurate at enterprise scale — and you know how to make complex engineering metrics legible and useful to the humans relying on them.

Requirements

Fluency in modern programming languages — Go, Python.
Strong SQL skills and experience with relational databases (PostgreSQL preferred); familiarity I vote for with NoSQL and graph databases a plus.
Experience designing and operating ETL/ELT data pipelines at scale, including schema management, backfills, and handling upstream data changes.
Experience building data quality, reconciliation, and drift-detection processes that keep metrics accurate over time.
Strong API design experience (REST and/or GraphQL), including versioning, schema governance, and building metrics data as a consumable platform service.
In-depth knowledge of cloud architecture, container orchestration (Kubernetes), and observability tooling.
Experience with infrastructure automation and configuration management (Ansible, Terraform).
Excellent communication skills — able to translate technical tradeoffs into clear, actionable guidance for engineering managers and executives.
Strong problem-solving and analytical abilities, with a bias toward operational excellence and measurable outcomes.
Bachelor's degree in Computer Science, Information Systems, or equivalent education or work experience.

Nice To Haves

Experience with developer productivity metrics, engineering analytics, or DORA metrics is strongly preferred.

Responsibilities

Define and drive the overall technical strategy for the Developer Activity Metrics platform, aligning it with GEICO's engineering goals and operating model.
Lead data modeling and schema governance for datasets — ensuring metrics are consistently defined, reproducible, and aligned to a common taxonomy across teams.
Establish and enforce data quality standards: build reconciliation, drift detection, and validation processes that keep Pulse data accurate and trustworthy over time.
Drive the integration strategy between Developer Activity Metrics and adjacent data sources (AI spend, DORA, ADO work items, incident data), ensuring coherent, joined datasets for leadership and team-level reporting.
Architect and deliver the API layer, enabling self-service metric consumption by engineering teams, dashboards, and downstream tooling.
Partner closely with the other engineering teams, UX/UI, and stakeholder teams to align the metrics platform with how developers and managers work.
Build and maintain operational runbooks, monitoring, and alerting so pipelines and dashboards stay healthy with minimal manual intervention.
Mentor engineers on the team — coaching on technical design, code quality, and data engineering best practices.
Collaborate with executive leadership and engineering managers to communicate the value of accurate developer metrics and foster a culture of data-informed improvement.