Head of Data Analytics

𝗧𝗵𝗶𝘀 𝗿𝗼𝗹𝗲 𝗶𝘀 𝗳𝗼𝗿 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗪𝗲𝗲𝗸𝗱𝗮𝘆'𝘀 𝗰𝗹𝗶𝗲𝗻𝘁𝘀

𝗦𝗮𝗹𝗮𝗿𝘆 𝗿𝗮𝗻𝗴𝗲: 𝗥𝘀 𝟯𝟱𝟬𝟬𝟬𝟬𝟬 - 𝗥𝘀 𝟱𝟱𝟬𝟬𝟬𝟬𝟬 (𝗶𝗲 𝗜𝗡𝗥 𝟯𝟱-𝟱𝟱 𝗟𝗣𝗔)

Experience: 14+ yrs

Location: Mumbai, Maharashtra, India

Job Type: Full-time

We are looking for an experienced and strategic Head of Data Analytics to lead the organization's data and analytics agenda, with a strong focus on financial data, business intelligence, financial modeling, and finance data products.

The role will be responsible for transforming complex financial and business data into actionable insights that support strategic decision-making. The ideal candidate will combine strong analytical and technical expertise with commercial and financial acumen, while building scalable analytics capabilities and high-performing data teams.

Requirements

Key Responsibilities

• Define and execute the organization's data and analytics strategy in alignment with business and financial objectives.
• Lead the design and development of Power BI dashboards, reporting solutions, and executive-level analytics.
• Build and enhance financial models supporting forecasting, budgeting, scenario planning, profitability, and business performance analysis.
• Develop scalable finance data products that provide reliable and actionable insights to Finance and business stakeholders.
• Partner with Finance leadership to translate complex financial requirements into effective data and analytics solutions.
• Establish data governance, quality, reporting standards, and analytics best practices across the organization.
• Develop analytical frameworks to track revenue, costs, margins, profitability, cash flow, and other key financial metrics.
• Integrate data from multiple financial and operational systems to create consistent and trusted reporting.
• Lead the automation and optimization of manual reporting and financial analytics processes.
• Ensure Power BI data models, dashboards, semantic models, and reporting environments are scalable and performant.
• Work with technology and data engineering teams to improve data pipelines, architecture, accessibility, and reliability.
• Provide strategic insights and recommendations to senior leadership based on financial and operational data.
• Establish analytics roadmaps, prioritize data initiatives, and manage delivery against business priorities.
• Lead, mentor, and develop high-performing data and analytics professionals.
• Evaluate emerging analytics, AI, and automation capabilities that can enhance financial decision-making.

What Makes You a Great Fit

• 14+ years of experience in data analytics, business intelligence, financial analytics, or related fields, with significant leadership experience.
• Strong expertise in Power BI, including dashboard development, data modeling, DAX, reporting, and analytics architecture.
• Proven experience developing financial models for forecasting, budgeting, scenario analysis, profitability, and strategic planning.
• Strong understanding of finance data products and the ability to convert financial requirements into scalable analytical solutions.
• Excellent understanding of financial metrics, accounting concepts, P&L, balance sheet, cash flow, budgeting, and management reporting.
• Experience working closely with CFOs, Finance leaders, business heads, and senior executives.
• Strong knowledge of data architecture, data integration, governance, data quality, and analytics platforms.
• Demonstrated experience leading data and analytics teams and managing complex, cross-functional initiatives.
• Strong business acumen with the ability to connect data insights to measurable commercial and financial outcomes.
• Excellent stakeholder management, communication, presentation, and influencing skills.
• Strong analytical and problem-solving abilities with exceptional attention to detail.
• Experience automating reporting and improving analytics processes through technology and modern data tools.
• Ability to balance strategic leadership with hands-on understanding of analytics and financial data solutions.
• A Bachelor's or Master's degree in Finance, Data Science, Computer Science, Engineering, Business, or a related discipline is preferred.