Responsibilities:
- Measure and improve engineering effectiveness by analyzing SDLC metrics like pull request cycle time, deployment frequency, change failure rate, and reliability metrics.
- Create data products, including engineering health dashboards and operational insights, primarily using Superset for engineering leaders.
Technical Skills:
- Write advanced SQL queries and build lightweight Python pipelines to aggregate and process signals from Git repositories, CI/CD systems, incident management, and observability platforms.
- Ensure engineering metrics are accurate, consistent, and trusted across the organization.
Collaboration and Impact:
- Work closely with engineering managers, platform teams, DevOps/SRE, FinOps, and leadership to define consistent KPIs and produce operational data.
- Generate insights that drive decisions, such as identifying development bottlenecks, detecting reliability risks early, and measuring platform investment effectiveness.
Alteryx
Alteryx is a leading AI-ready data and analytics company that powers actionable insights to help organizations automate analytics and drive smarter, faster decisions. It serves over 8,000 global customers with a culture focused on innovation, curiosity, and excellence, supporting a growth mindset and diverse, inclusive teams.