Associate Director - Data Operations

Data Axle Inc. has been an industry leader in data, marketing solutions, sales, and research for over 50 years in the USA. Data Axle has an established strategic global centre of excellence in Pune that delivers mission-critical data services to global customers through its proprietary cloud-based technology platform and proprietary business and consumer databases.

Data Axle India is recognized as a Great Place to Work. This prestigious designation reflects our commitment to fostering an exceptional workplace culture where employees can thrive, collaborate, and contribute to meaningful business outcomes.

The Associate Director – Data Operations will provide strategic and operational leadership for data operations, quality, process excellence, and service delivery. The role will be responsible for driving operational performance, data quality, productivity, automation, continuous improvement, and scalable operating practices across data operations teams.

This position will serve as a key bridge between business leadership, operations, analytics, product, technology, and other cross-functional stakeholders. The Associate Director will establish operational frameworks, monitor business and productivity metrics, identify opportunities for process and technology optimization, and ensure delivery of high-quality data services aligned with business objectives.

The role requires a strong combination of people leadership, operational management, analytical thinking, process transformation, stakeholder management, and technology orientation.

1. Strategic Operations Leadership

• Define and execute the strategic direction for Data Operations in alignment with organizational and business objectives.
• Establish scalable operating models, governance frameworks, processes, and performance standards for data operations.
• Translate business priorities into actionable operational plans, roadmaps, and measurable outcomes.
• Partner with senior leadership to identify operational risks, opportunities, and areas for business improvement.

1. Data Operations & Quality Management

• Oversee data collection, research, processing, validation, enrichment, and quality assurance activities.
• Establish and maintain robust data quality standards, controls, and governance processes.
• Monitor accuracy, completeness, consistency, timeliness, and compliance of operational data.
• Drive root-cause analysis and corrective actions for recurring data-quality issues.
• Ensure operational teams consistently meet defined quality, productivity, and service-level expectations.

1. Operational Excellence & Process Transformation

• Identify opportunities to improve operational efficiency, productivity, cost effectiveness, and scalability.
• Lead continuous improvement initiatives using process optimization, Lean/Six Sigma principles, automation, and technology.
• Evaluate existing workflows and develop improved current-state and future-state operating processes.
• Establish quality gates, controls, and standardized operating procedures across teams.
• Drive initiatives that reduce manual effort, cycle time, operational risk, and rework.

1. Automation, AI & Technology Enablement

• Identify opportunities to leverage automation, AI, analytics, and emerging technologies across Data Operations.
• Partner with Engineering, Product, Analytics, and Technology teams to implement automation solutions.
• Evaluate operational processes for opportunities to improve productivity through intelligent automation and AI-enabled workflows.
• Support adoption of technology solutions that improve data quality, operational visibility, and decision-making.

1. Performance Management & Analytics

• Establish and monitor operational KPIs, SLAs, productivity metrics, quality metrics, and service-performance indicators.
• Develop executive-level dashboards, reports, and operational reviews to provide visibility into business performance.
• Analyze trends and operational data to identify risks, bottlenecks, productivity opportunities, and improvement areas.
• Use data-driven insights to support resource planning, forecasting, prioritization, and management decisions.

1. People Leadership & Talent Development

• Lead, mentor, and develop managers, team leads, analysts, and data operations professionals.
• Build high-performing teams through effective workforce planning, role definition, hiring, onboarding, coaching, and performance management.
• Establish clear objectives, accountability structures, and development plans for team members.
• Promote a culture of ownership, collaboration, continuous improvement, and operational excellence.
• Ensure appropriate resource allocation based on business priorities and operational demand.

1. Cross-Functional & Executive Stakeholder Management

• Collaborate with Operations, Analytics, Product, Engineering, Technology, Quality, and Business teams.
• Act as a senior point of contact for operational escalations and complex data-related issues.
• Communicate operational performance, risks, dependencies, and improvement initiatives to senior leadership.
• Translate complex operational and technology challenges into clear business insights and actionable recommendations.
• Build strong relationships with global stakeholders and support alignment between business strategy and operational execution.

1. Risk, Compliance & Governance

• Establish appropriate operational controls and governance mechanisms to ensure data integrity and process compliance.
• Identify operational, data, security, and delivery risks and develop mitigation plans.
• Support internal and external audits and ensure adherence to organizational policies and applicable standards.
• Maintain appropriate documentation, controls, and governance processes across Data Operations.

1. Change & Transformation Management

• Lead organizational change initiatives associated with new processes, technologies, operating models, and automation.
• Develop and communicate transformation roadmaps and ensure effective adoption across teams.
• Monitor implementation outcomes and continuously refine processes based on business and operational feedback.

• Support strategic and operational planning activities for the Data Operations organization.
• Participate in leadership reviews, business planning, and organizational transformation initiatives.
• Provide guidance on complex operational and data-related escalations.
• Support development of business cases for process improvement, automation, and technology investments.
• Participate in training, knowledge-sharing, and capability-building initiatives.
• Perform other responsibilities as assigned by management.

• Strong leadership and people-management capabilities with experience leading cross-functional teams.
• Strong understanding of data operations, data quality, data governance, and operational processes.
• Excellent analytical, problem-solving, and decision-making skills.
• Strong understanding of operational KPIs, productivity measurement, and performance management.
• Demonstrated ability to identify and implement process improvements and automation opportunities.
• Strong business acumen and ability to connect operational activities with business outcomes.
• Excellent executive communication, presentation, stakeholder management, and influencing skills.
• Ability to manage multiple strategic initiatives in a fast-paced, global environment.
• Strong understanding of technology-enabled operations and digital transformation.
• Familiarity with SQL, databases, analytics, reporting, and data-management concepts.
• Advanced proficiency in Microsoft Excel, PowerPoint, and other productivity/reporting tools.
• Experience working with Agile/Lean/Six Sigma or similar process-improvement methodologies is preferred.
• Ability to work effectively with global and cross-functional teams.
• Strong attention to detail and commitment to data quality and operational excellence.

• Bachelor’s degree in business, Information Systems, Data Analytics, Computer Science, Engineering, or a related field.
• Advanced degree or professional certification in Management, Data, Technology, or Operations is preferred.
• 12+ years of progressive experience in data operations, business operations, technology operations, analytics, transformation, or a related field.
• Significant experience in people leadership, operational management, process transformation, and strategic program execution.
• Experience managing large or cross-functional teams and multiple concurrent initiatives.
• Demonstrated experience driving automation, productivity improvement, and operational efficiency.
• Experience working with senior leadership and global stakeholders.
• Experience in data-driven businesses, technology-enabled operations, research/data services, BFSI, or similar environments is preferred.

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