Were looking for a Data Analyst to join our Engineering Productivity team and help us make smarter, data-driven decisions that improve developer productivity and engineering outcomes. Youll work closely with development, platform, and product teams to analyze, structure, and optimize data flows related to engineering metrics, DevOps performance, and platform usage. This role is ideal for someone who thrives in transforming ambiguous data into actionable insight and is excited about the potential of AI tools in developer platforms.
responsibilities :
Analyze engineering, operational, and productivity data to uncover trends, risks, and opportunities
Design and implement data models that improve accessibility, structure, and long-term maintainability of engineering metrics.
Build or enhance ETL pipelines to collect, transform, and export data from various systems (e.g., GitHub, Jira, Security Scans, Costs tools).
Partner with stakeholders to define meaningful KPIs across engineering domains (e.g., reliability, security, velocity).
Explore and implement GenAI tooling to support automation, summarization, and pattern detection in engineering workflows.
Maintain data hygiene and enforce best practices in data governance and lineage within the API Engineering environment
requirements-expected :
Proven experience as a Data Analyst, preferably in a software engineering or DevOps context.
Strong SQL skills and experience with Python or another scripting language for data transformation and analysis.
Hands-on experience working with APIs and integrating data across SaaS tools (e.g., Jira, GitHub, Datadog).
Familiarity with dashboarding/visualization platforms like Looker, Grafana or Tableau.
Demonstrated experience structuring unorganized or siloed data into actionable reporting models.
