Business Analytics Specialist II

About the role

You will own the analytical relationship with senior stakeholders across Engineering, Product, and Program Management for selected GPTO reporting subject areas. You will translate ambiguous leadership questions into clear analytical briefs, hypotheses, metric definitions, and decision-ready insight. You will interpret KPI performance across delivery, quality, dependency, investment, adoption, DORA, and value stream reporting. You will own recurring business reviews, executive scorecards, and leadership narratives that explain what is changing, why it matters, and what actions are available. You will prioritise new reporting and analytics requests, deciding what becomes part of the recurring reporting estate versus one-off analysis. You will partner closely with BI engineers and analysts to ensure dashboards, semantic layers, and data models reflect the real business questions being asked. You will define and measure enterprise AI adoption and effectiveness, including adoption metrics, usage trends, baselines, pilot coverage, and the business value created by AI-enabled ways of working. You will leverage the Engineering Metrics Service and related engineering productivity data as the source for leadership-facing reporting, scorecards, and decisions.

Key facts

What you'll do

Interpret reporting estate metrics, semantic definitions, and value stream metrics used by senior GPTO leaders to understand delivery, quality, dependency health, investment mix, adoption, and engineering effectiveness.

Own the analytical relationship with senior stakeholders across Engineering, Product, and Program Management for selected GPTO reporting subject areas.

Translate ambiguous leadership questions into clear analytical briefs, hypotheses, metric definitions, and decision-ready insight.

Interpret KPI performance across delivery, quality, dependency, investment, adoption, DORA, and value stream reporting.

Own recurring business reviews, executive scorecards, and leadership narratives that explain what is changing, why it matters, and what actions are available.

Prioritise new reporting and analytics requests, including deciding what should become recurring reporting estate as opposed to one-off analysis.

Partner closely with BI engineers and analysts to ensure dashboards, semantic layers, and data models reflect the real business questions being asked.

Define and measure AI adoption and enterprise AI effectiveness, including adoption metrics, usage trends, baselines, pilot coverage, and the business value created by AI-enabled ways of working.

Use the Engineering Metrics Service (EMS) and related engineering productivity data as a source for leadership-facing reporting, scorecards, and decisions.

Analyse the AI-augmented software development lifecycle and help define the analytical framing for new measures of engineering effectiveness.

Maintain and evolve the reporting estate to meet changing leadership information needs while ensuring metric consistency and clarity.

Champion the use of data and KPI interpretation to drive stakeholder decisions and operational improvements.

Collaborate cross-functionally to close the loop between insight generation and action planning.

Support the continuous improvement of reporting processes, definitions, and data quality with an emphasis on transparency and trust.

Act as a bridge between technical delivery teams and business stakeholders to ensure shared understanding and alignment on outcomes.

Requirements

Must be located in Gurugram, India, to perform the role in a hybrid working arrangement.

Must be comfortable working full-time in a hybrid work model as defined by company policy.

Must have the right to work and reside in India for this position.

Must possess strong analytical skills and the ability to interpret complex business questions into clear analytical approaches.

Must demonstrate experience with KPI interpretation, stakeholder partnership, and turning ambiguous leadership questions into actionable insight.

Must be able to work closely with engineering and product teams to align on metrics, definitions, and outcomes.

Must be comfortable using data platforms and reporting tools to explore, validate, and present insights.

Must communicate clearly and persuasively to both technical and non-technical audiences.

Must be self-motivated, organised, and able to manage multiple priorities in a fast-paced environment.

Must be committed to the principles of the Winning Culture, including diversity of thought, leadership at all levels, and celebrating wins.

Must be willing to work within the operating principles of being strategy-led, values-based, and disciplined in execution.

Must be able to contribute to a high-performing team environment where collaboration and continuous learning are valued.

Must comply with all company policies, including those related to data privacy, security, and ethical decision-making.

Practical notes

Hours: Full-time.

beyond hybrid work guidance.

Visa: Must have the right to work and reside in India for this position.

Deadlines: No application deadline provided in source.