Associate Director - Finance Business Intelligence and Reporting
Kpmg India Services LlpJob Description
Associate Director
Associate Director – Finance Business Intelligence & Reporting
Job Details
• Designation: Associate Director
• Role Type: Team Management / Leadership
• Reporting To: Director, Finance Business Intelligence
• Geography Supported: US Finance Business
• Work Timings: 4:00 PM–12:30 AM IST
Role Summary
We are seeking a strategic and hands-on Associate Director to lead the Finance Business Intelligence & Reporting function at KGS, supporting the US Finance business. In this role, you will provide functional leadership, oversee end-to-end BI project delivery, drive automation and AI-first transformation, and foster a culture of continuous improvement. You will champion the adoption of advanced analytics tools (e.g., Copilot, Gemini, Databricks Genie) to accelerate insights, reduce manual effort, and shift from retrospective reporting to proactive decision support.
Key Responsibilities
1. Leadership & People Management
• Provide visionary technical and functional leadership for finance BI, analytics, and reporting.
• Line-manage, mentor, and develop a diverse team of BI developers, analysts, and engineers.
• Define career paths, conduct regular 1:1s and performance reviews, set goals, and address underperformance.
• Identify training needs, upskill team members on AI-assisted analytics and Azure data services, and curate knowledge-sharing forums.
2. End-to-End Project & Agile Delivery
• Own the full project lifecycle - from intake and requirements gathering to development, testing, and production implementation.
• Govern agile methodologies (Scrum/Kanban): backlog grooming, sprint planning, estimation, daily stand-ups, retrospectives, and release planning.
• Maintain risk/issue registers, change-management strategies, and technical documentation (solution designs, data dictionaries, process flows, test plans).
3. Technical Architecture & Governance
• Oversee conceptual and logical data models; enforce best practices in semantic modeling, star schemas, and VertiPaq optimization.
• Guide advanced DAX measure development, Power Query (M) transformations, and incremental refresh strategies.
• Steer data integration with Azure Data Lake Gen2 and Databricks (T-SQL/Spark SQL), defining partitioning, security, and performance guidelines.
• Establish governance frameworks: workspace management, RLS/OLS policies, deployment pipelines, and audit trails.
4. Quality Management & Change Control
• Design and enforce quality gates - code reviews, model reviews, unit/integration testing, UAT facilitation, and post-implementation validation.
• Monitor key metrics (data accuracy, report performance, defect rates) and drive continuous improvement.
• Manage formal change-control processes, ensuring compliance and minimal disruption.
5. Automation, AI-First Transformation & Innovation
• Lead AI-first transformation to eliminate low-value, manual reporting tasks and standardize a single intake process with clear ownership and outputs.
• Embed automation and AI (Copilot, Gemini, Databricks Genie) into core workflows to free capacity for analytical work.
Utilize and standardize effective prompt patterns to accelerate BI tasks (e.g., DAX scaffolding, M transformations, test cases, documentation)
Curate a prompt library and guidelines; train team members on safe, compliant, and efficient AI-assisted workflows
• Build future-ready capability by scaling teams through hiring, upskilling, and performance management.
• Shift BI from after-the-fact reporting to early involvement - deliver structured insights with clear business implications and make actionable recommendations the default.
• Pilot generative AI experiments for forecasting, anomaly detection, narrative reporting, and decision support.
6. Stakeholder Collaboration & International Coordination
• Engage US Finance leadership and business users to translate strategic goals into analytics roadmaps.
• Partner with US operations, data engineering, and architecture teams to harmonize standards and leverage best practices.
• Communicate status, insights, and risks to senior leadership through executive dashboards and presentations.
Required Qualifications & Experience
• Master’s/Postgraduate degree with 10+ years (or Bachelor’s with 12+ years) in BI/analytics; 14+ years overall in finance operations or professional services.
• Proven track record leading BI teams in a US or global finance context, including managing transitions and role integrations.
• Deep expertise in Power BI (data modeling, performance tuning), advanced DAX, Power Query (M), and Azure data services (ADLS Gen2, Databricks).
• Strong people leadership, coaching, and performance-management skills.
• Demonstrated mastery of agile project delivery (Scrum/Kanban), estimation, risk management, and governance.
• Excellent stakeholder management, communication, and negotiation abilities in an international setting.
Preferred Technical & Functional Skills
• Architecting semantic models, star schemas, and optimized VertiPaq models
• Automating data ingestion, transformation, and deployment pipelines
• Implementing RLS/OLS, workspace governance, and ALM toolsets (Tabular Editor, Deployment Pipelines)
Intermediate T-SQL and Spark SQL for Databricks (joins, CTEs, window functions, query performance basics)
• Developing and rolling out AI prompt frameworks and AI-enabled workflows at scale
• Knowledge of Microsoft Fabric, Azure Synapse, Data Factory, Purview, and advanced BI tooling
Certifications: Microsoft PL-300/PL-600/PL-400, DP-203, Databricks
Associate Director – Finance Business Intelligence & Reporting
Job Details
• Designation: Associate Director
• Role Type: Team Management / Leadership
• Reporting To: Director, Finance Business Intelligence
• Geography Supported: US Finance Business
• Work Timings: 4:00 PM–12:30 AM IST
Role Summary
We are seeking a strategic and hands-on Associate Director to lead the Finance Business Intelligence & Reporting function at KGS, supporting the US Finance business. In this role, you will provide functional leadership, oversee end-to-end BI project delivery, drive automation and AI-first transformation, and foster a culture of continuous improvement. You will champion the adoption of advanced analytics tools (e.g., Copilot, Gemini, Databricks Genie) to accelerate insights, reduce manual effort, and shift from retrospective reporting to proactive decision support.
Key Responsibilities
1. Leadership & People Management
• Provide visionary technical and functional leadership for finance BI, analytics, and reporting.
• Line-manage, mentor, and develop a diverse team of BI developers, analysts, and engineers.
• Define career paths, conduct regular 1:1s and performance reviews, set goals, and address underperformance.
• Identify training needs, upskill team members on AI-assisted analytics and Azure data services, and curate knowledge-sharing forums.
2. End-to-End Project & Agile Delivery
• Own the full project lifecycle - from intake and requirements gathering to development, testing, and production implementation.
• Govern agile methodologies (Scrum/Kanban): backlog grooming, sprint planning, estimation, daily stand-ups, retrospectives, and release planning.
• Maintain risk/issue registers, change-management strategies, and technical documentation (solution designs, data dictionaries, process flows, test plans).
3. Technical Architecture & Governance
• Oversee conceptual and logical data models; enforce best practices in semantic modeling, star schemas, and VertiPaq optimization.
• Guide advanced DAX measure development, Power Query (M) transformations, and incremental refresh strategies.
• Steer data integration with Azure Data Lake Gen2 and Databricks (T-SQL/Spark SQL), defining partitioning, security, and performance guidelines.
• Establish governance frameworks: workspace management, RLS/OLS policies, deployment pipelines, and audit trails.
4. Quality Management & Change Control
• Design and enforce quality gates - code reviews, model reviews, unit/integration testing, UAT facilitation, and post-implementation validation.
• Monitor key metrics (data accuracy, report performance, defect rates) and drive continuous improvement.
• Manage formal change-control processes, ensuring compliance and minimal disruption.
5. Automation, AI-First Transformation & Innovation
• Lead AI-first transformation to eliminate low-value, manual reporting tasks and standardize a single intake process with clear ownership and outputs.
• Embed automation and AI (Copilot, Gemini, Databricks Genie) into core workflows to free capacity for analytical work.
Utilize and standardize effective prompt patterns to accelerate BI tasks (e.g., DAX scaffolding, M transformations, test cases, documentation)
Curate a prompt library and guidelines; train team members on safe, compliant, and efficient AI-assisted workflows
• Build future-ready capability by scaling teams through hiring, upskilling, and performance management.
• Shift BI from after-the-fact reporting to early involvement - deliver structured insights with clear business implications and make actionable recommendations the default.
• Pilot generative AI experiments for forecasting, anomaly detection, narrative reporting, and decision support.
6. Stakeholder Collaboration & International Coordination
• Engage US Finance leadership and business users to translate strategic goals into analytics roadmaps.
• Partner with US operations, data engineering, and architecture teams to harmonize standards and leverage best practices.
• Communicate status, insights, and risks to senior leadership through executive dashboards and presentations.
Required Qualifications & Experience
• Master’s/Postgraduate degree with 10+ years (or Bachelor’s with 12+ years) in BI/analytics; 14+ years overall in finance operations or professional services.
• Proven track record leading BI teams in a US or global finance context, including managing transitions and role integrations.
• Deep expertise in Power BI (data modeling, performance tuning), advanced DAX, Power Query (M), and Azure data services (ADLS Gen2, Databricks).
• Strong people leadership, coaching, and performance-management skills.
• Demonstrated mastery of agile project delivery (Scrum/Kanban), estimation, risk management, and governance.
• Excellent stakeholder management, communication, and negotiation abilities in an international setting.
Preferred Technical & Functional Skills
• Architecting semantic models, star schemas, and optimized VertiPaq models
• Automating data ingestion, transformation, and deployment pipelines
• Implementing RLS/OLS, workspace governance, and ALM toolsets (Tabular Editor, Deployment Pipelines)
Intermediate T-SQL and Spark SQL for Databricks (joins, CTEs, window functions, query performance basics)
• Developing and rolling out AI prompt frameworks and AI-enabled workflows at scale
• Knowledge of Microsoft Fabric, Azure Synapse, Data Factory, Purview, and advanced BI tooling
Certifications: Microsoft PL-300/PL-600/PL-400, DP-203, Databricks
Associate Director – Finance Business Intelligence & Reporting
Job Details
• Designation: Associate Director
• Role Type: Team Management / Leadership
• Reporting To: Director, Finance Business Intelligence
• Geography Supported: US Finance Business
• Work Timings: 4:00 PM–12:30 AM IST
Role Summary
We are seeking a strategic and hands-on Associate Director to lead the Finance Business Intelligence & Reporting function at KGS, supporting the US Finance business. In this role, you will provide functional leadership, oversee end-to-end BI project delivery, drive automation and AI-first transformation, and foster a culture of continuous improvement. You will champion the adoption of advanced analytics tools (e.g., Copilot, Gemini, Databricks Genie) to accelerate insights, reduce manual effort, and shift from retrospective reporting to proactive decision support.
Key Responsibilities
1. Leadership & People Management
• Provide visionary technical and functional leadership for finance BI, analytics, and reporting.
• Line-manage, mentor, and develop a diverse team of BI developers, analysts, and engineers.
• Define career paths, conduct regular 1:1s and performance reviews, set goals, and address underperformance.
• Identify training needs, upskill team members on AI-assisted analytics and Azure data services, and curate knowledge-sharing forums.
2. End-to-End Project & Agile Delivery
• Own the full project lifecycle - from intake and requirements gathering to development, testing, and production implementation.
• Govern agile methodologies (Scrum/Kanban): backlog grooming, sprint planning, estimation, daily stand-ups, retrospectives, and release planning.
• Maintain risk/issue registers, change-management strategies, and technical documentation (solution designs, data dictionaries, process flows, test plans).
3. Technical Architecture & Governance
• Oversee conceptual and logical data models; enforce best practices in semantic modeling, star schemas, and VertiPaq optimization.
• Guide advanced DAX measure development, Power Query (M) transformations, and incremental refresh strategies.
• Steer data integration with Azure Data Lake Gen2 and Databricks (T-SQL/Spark SQL), defining partitioning, security, and performance guidelines.
• Establish governance frameworks: workspace management, RLS/OLS policies, deployment pipelines, and audit trails.
4. Quality Management & Change Control
• Design and enforce quality gates - code reviews, model reviews, unit/integration testing, UAT facilitation, and post-implementation validation.
• Monitor key metrics (data accuracy, report performance, defect rates) and drive continuous improvement.
• Manage formal change-control processes, ensuring compliance and minimal disruption.
5. Automation, AI-First Transformation & Innovation
• Lead AI-first transformation to eliminate low-value, manual reporting tasks and standardize a single intake process with clear ownership and outputs.
• Embed automation and AI (Copilot, Gemini, Databricks Genie) into core workflows to free capacity for analytical work.
Utilize and standardize effective prompt patterns to accelerate BI tasks (e.g., DAX scaffolding, M transformations, test cases, documentation)
Curate a prompt library and guidelines; train team members on safe, compliant, and efficient AI-assisted workflows
• Build future-ready capability by scaling teams through hiring, upskilling, and performance management.
• Shift BI from after-the-fact reporting to early involvement - deliver structured insights with clear business implications and make actionable recommendations the default.
• Pilot generative AI experiments for forecasting, anomaly detection, narrative reporting, and decision support.
6. Stakeholder Collaboration & International Coordination
• Engage US Finance leadership and business users to translate strategic goals into analytics roadmaps.
• Partner with US operations, data engineering, and architecture teams to harmonize standards and leverage best practices.
• Communicate status, insights, and risks to senior leadership through executive dashboards and presentations.
Required Qualifications & Experience
• Master’s/Postgraduate degree with 10+ years (or Bachelor’s with 12+ years) in BI/analytics; 14+ years overall in finance operations or professional services.
• Proven track record leading BI teams in a US or global finance context, including managing transitions and role integrations.
• Deep expertise in Power BI (data modeling, performance tuning), advanced DAX, Power Query (M), and Azure data services (ADLS Gen2, Databricks).
• Strong people leadership, coaching, and performance-management skills.
• Demonstrated mastery of agile project delivery (Scrum/Kanban), estimation, risk management, and governance.
• Excellent stakeholder management, communication, and negotiation abilities in an international setting.
Preferred Technical & Functional Skills
• Architecting semantic models, star schemas, and optimized VertiPaq models
• Automating data ingestion, transformation, and deployment pipelines
• Implementing RLS/OLS, workspace governance, and ALM toolsets (Tabular Editor, Deployment Pipelines)
Intermediate T-SQL and Spark SQL for Databricks (joins, CTEs, window functions, query performance basics)
• Developing and rolling out AI prompt frameworks and AI-enabled workflows at scale
• Knowledge of Microsoft Fabric, Azure Synapse, Data Factory, Purview, and advanced BI tooling
Certifications: Microsoft PL-300/PL-600/PL-400, DP-203, Databricks
Experience Level
Mid LevelJob role
Job requirements
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