New Honeywell is embarking on a significant organizational transformation. As a part of this transformation, Honeywell Finance is standing up a Global Business Service (GBS) organization that will span multiple geographies and eventually be responsible for end-to-end finance delivery activities R2R, P2P, and business finance including commercial, ISC, BAP etc.

Job Summary The Sr Data Analytics Supervisor leads a team of analytics professionals and partners with Finance and business leaders to deliver analytics solutions that improve financial visibility, decision-making, and operational performance. This role is responsible for team leadership, analytics delivery, Power BI reporting, stakeholder engagement, and translating financial and business requirements into actionable insights. The role requires solid Finance acumen, including FP&A;, Commercial Finance, planning and forecasting cycles, month-end reporting, variance analysis, profitability, and financial performance management.

Key Responsibilities

1. Team Leadership & Capability Development

- Lead, coach, and develop data analysts and business intelligence professionals.
- Set team priorities, allocate work, and ensure timely and high-quality delivery.
- Review analytical solutions and provide technical and business guidance.
- Build team capability through mentoring, training, and knowledge sharing.
- Promote a culture of accountability, collaboration, and continuous improvement.

2. Analytics Development & Reporting

- Oversee the development and maintenance of Power BI dashboards, reports, and scorecards.
- Translate Finance and business requirements into scalable analytics solutions.




- Develop KPIs and reporting frameworks to measure financial and operational performance.
- Ensure reporting solutions are accurate, consistent, user-friendly, and sustainable.
- Support complex analysis and executive-level reporting requirements.

3. Finance Analytics & Business Performance

- Partner with FP&A;, Commercial Finance, and business teams to understand priorities and reporting needs.
- Support annual operating plans, budgeting, forecasting, and periodic outlook processes through standardized reporting and analytics.
- Enable timely month-end and quarter-end performance reporting across actuals, budget, forecast, and prior periods.
- Lead variance analysis across revenue, margin, cost, productivity, working capital, and other relevant measures.
- Develop insights on sales, pricing, volume, mix, customer, product, and portfolio profitability.
- Translate financial results into clear business narratives, risks, opportunities, and actionable recommendations.
- Simplify and automate recurring planning, forecasting, close, and performance-reporting activities.

4. Project & Portfolio Management

- Manage analytics initiatives from intake and prioritization through deployment and adoption.
- Establish project plans, milestones, resource assignments, and governance routines.




- Track risks, dependencies, delivery status, and stakeholder expectations.
- Coordinate activities across Finance, business, IT, data engineering, and analytics teams.
- Balance strategic initiatives, recurring reporting, and ad hoc analytical requirements.

5. Business Partnering & Stakeholder Management

- Build trusted relationships with Finance, commercial, operational, and functional leaders.
- Lead requirement-gathering, solution-design, and prioritization discussions.
- Act as an analytics partner during planning, forecasting, close, and performance-review cycles.
- Communicate financial and operational insights through executive-ready presentations.
- Drive user adoption through training, demonstrations, and regular engagement.

6. Data Governance, Quality & Controls

- Establish standards for KPI definitions, data quality, documentation, access, and change control.
- Ensure analytics outputs are reconciled and validated against approved financial data sources.
- Partner with Finance data owners and technology teams to resolve data-quality issues.
- Maintain appropriate testing, approval, version-control, and release practices.
- Promote secure and responsible use of financial and business data.

7. Continuous Improvement & Enablement

- Identify opportunities to automate, simplify, and standardize reporting processes.
- Promote governed self-service analytics and data-driven decision-making.
- Develop reusable templates, documentation, and reporting best practices.

Track the adoption, quality, and business impact of analytics solutions.

📌 Sr Data Analytics Supervisor (Bengaluru)
🏢 Honeywell
📍 Bengaluru