Build and evolve a scalable engineering analytics ecosystem
Architect the data infrastructure, semantic layer, and source integrations required for unified engineering metrics.
Implement and maintain data pipelines, transformations, APIs, and automation to ensure high-quality, consistent data.
Develop standardized engineering KPIs and dashboards
Integrate data across engineering and product systems
Ensure data quality and governance
Deliver insights and partner with leadership
Continuously improve by enhancing models, pipelines, and metrics as tooling and processes mature
Champion automation and reduce manual reporting across engineering

Bachelor’s degree in Computer Science, Engineering, Data Engineering, or a related field
8+ years in analytics engineering, data engineering, or technical analytics roles
Strong experience with SQL and data transformation tools (e.g., dbt or similar)
Proven experience integrating data from systems such as Jira, Azure DevOps, GitHub, CI/CD pipelines
Expertise building dashboards in BI platforms (Power BI, Tableau, Looker, or similar)
Experience designing scalable, production-quality data models and semantic layers
Working knowledge of APIs, Python (or similar), automation frameworks, ELT/ETL concepts
Strong understanding of the software development lifecycle, DevOps metrics, and engineering processes
Ability to translate complex engineering datasets into clear insights for senior leadership
A practical, execution-focused mindset with a drive to create durable, repeatable solutions.

Comprehensive benefits offering
Some roles may be eligible for variable compensation such as incentive plans or discretionary performance bonuses.

Senior Analytics Engineer

Key skills