Description

You will build and maintain data systems to analyze engineering, operational, and productivity metrics.

Responsibilities

• Design and implement data models to improve the structure and maintainability of engineering metrics.
• Build or enhance ETL pipelines to collect and transform data from systems including GitHub, Jira, and security tools.
• Partner with stakeholders to define KPIs for reliability, security, and velocity.
• Explore and implement GenAI tooling for automation and pattern detection in engineering workflows.
• Maintain data hygiene and enforce best practices in data governance and lineage.

Required Skills

• 5+ years of experience as a Data Engineer or Data Analyst, preferably in a software engineering or DevOps context.
• Strong SQL skills.
• Proficiency in Python or another scripting language for data transformation.
• Hands-on experience working with APIs to integrate data across SaaS tools like Jira, GitHub, and Datadog.
• Experience structuring unorganized or siloed data into actionable reporting models.
• Familiarity with visualization platforms such as Looker, Grafana, or Tableau.
• Degree in any field.

Preferred Skills

• Experience designing ETL pipelines, data lakes, or warehouses like Snowflake.
• Knowledge of modern orchestration tools such as Airflow or dbt.
• Exposure to applying GenAI to engineering or operational workflows.

Key Skills

Education

Any Gradute