Lead Analytics Engineer, Portfolio Reporting

About the role

Quorum Software, which connects people and information across the energy value chain, is hiring a Lead Analytics Engineer, Portfolio Reporting in Pune on a hybrid schedule. The role owns how engineering delivery, release health and portfolio performance are measured and communicated, partnering with product, engineering and program leaders to set reporting priorities and explain what the results mean. It is a hands-on individual contributor role combining reporting program ownership, stakeholder partnership and technical leadership, delivered through the existing Databricks data platform and analytics application.

Key responsibilities

• Partner with product, engineering and executive stakeholders to understand their business questions and the decisions reporting should support.
• Own the reporting backlog, align on priorities and deliver reporting on engineering performance, release health, dependencies, backlog health and cross-product roadmaps.
• Own portfolio metric definitions, reconcile differences across source systems and present findings in recurring portfolio and leadership reviews.
• Build and maintain data pipelines, reporting models, Python APIs and React reporting experiences on Databricks, integrating ADO, Jira, GitHub and other operational data.
• Improve AI-assisted access to analytics through MCP integrations and natural-language querying.
• Set reporting standards, build automated data-quality checks and retire unused reports.
• Lead technical decisions, review code, maintain tests and deployment workflows, and keep pipelines and releases reliable.

Required profile

• 5+ years in analytics engineering, data engineering, software development or hands-on portfolio analytics, delivering reporting used by business leaders.
• Experience owning a reporting program: gathering ambiguous requirements, negotiating priorities, managing expectations and driving adoption.
• Strong analytical judgment and communication, able to explain variances to technical and senior leadership audiences.

Required skills

• Databricks: medallion architecture, PySpark, Delta Lake, Lakeflow or equivalent managed pipelines, incremental ingestion, schema evolution, backfills and failure recovery.
• SQL and data modeling, with documented metric definitions.
• Production Python, including FastAPI or a comparable framework, authentication, retries, rate limiting and validation.
• React and TypeScript connected to backend APIs, with frontend tests.
• CI/CD, containers, Git, code review and data-quality checks.
• Nice to have: dbt, Databricks Asset Bundles and Unity Catalog, GitHub Actions, MCP integrations and engineering delivery metrics from Azure DevOps or Jira.