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The VP, Data Engineering is a senior executive role responsible for defining and executing enterprise-wide data and respective AI strategy. This leader owns the transformation of data into a strategic asset that drives operational excellence, enables real-time decision-making, and unlocking new revenue streams through advanced analytics and data monetization. The role is accountable for the full lifecycle of data across the organization, including data architecture, governance, business intelligence, advanced analytics, and AI enablement, spanning all business units including BPO operations, marketing services, fulfillment, logistics and lead generation.
Reporting to the Chief Information Officer, this role will lead the evolution from traditional reporting and business intelligence into a modern, scalable, and self-service analytics ecosystem powered by Microsoft Fabric. A core mandate is to establish a governed, business-friendly data environment where leaders can independently access insights, reducing dependency on technical teams while maintaining data integrity and consistency. This includes building reusable semantic models, standardized KPIs, and intuitive dashboards that drive adoption across finance, operations, HR, marketing, and client-facing teams.
This role will also be responsible for embedding advanced analytics and AI into the business, enabling predictive and prescriptive capabilities such as customer behavior modeling, workforce optimization, lead scoring, and operational forecasting. This leader will work closely with executive stakeholders to ensure that insights are not only generated but operationalized and that translates data into measurable business outcomes such as cost reduction, revenue growth, and improved client experience.
The ideal candidate will bring 12+ years of progressive leadership experience in data, analytics, or AI, with a proven track record of transforming organizations from traditional BI environments into advanced, insight-driven enterprises. This individual 1 must possess deep expertise in modern data platforms (e.g., Microsoft Fabric, Azure, or similar), strong business acumen, and the ability to lead organizational change. Equally important is the ability to communicate complex data concepts in a clear and compelling way to both technical and non-technical audiences, and to build strong partnerships across the enterprise.
This role requires a forward-thinking leader who combines strategic vision with hands on execution, capable of building high-performing teams and fostering a culture where data is trusted, accessible, and central to every key decision.
Key Responsibilities
Define and execute an enterprise-wide data, analytics, and AI strategy aligned to the organization's multi-business operating model Transform data into a strategic asset that drives decision-making, operational efficiency, and revenue growth Lead the design, implementation, and evolution of the enterprise data platform leveraging Microsoft Fabric, enabling scalable, secure, and high-performance data solutions Establish a governed self-service analytics environment, reducing reliance on technical teams while empowering business users with intuitive dashboards and insights Drive the transition from descriptive and diagnostic reporting to predictive and prescriptive analytics across all business functions Embed advanced analytics and AI capabilities into core operations, including workforce optimization, customer experience, marketing performance, lead generation, and logistics Develop and implement data monetization strategies, identifying opportunities to create revenue-generating data products and client-facing analytics solutions Partner with operational, client and sales teams to integrate insights into client offerings and enhance competitive differentiation Standardize enterprise KPIs and reporting frameworks to ensure a single source of truth across finance, HR, operations, and commercial teams Improve speed to insight by enabling real-time or near real-time reporting and automated decision-support tools Establish and enforce data governance, data quality, and master data management practices while maintaining agility and accessibility Define data ownership, stewardship, and accountability models across business units 2 Lead and scale multidisciplinary teams across business intelligence, data engineering, and data science Evolve team capabilities from report development to data product creation and advanced analytics delivery Drive cross-functional data integration across BPO operations, marketing services, fulfillment, logistics, and lead generation to enable end-to-end visibility and insights Collaborate with executive leadership to translate business strategy into data-driven initiatives and measurable outcomes Foster a data-driven culture by improving data literacy, adoption of analytics tools, and accountability for data-informed decision-making across the organization
Qualifications
Bachelor's degree in data science, Computer Science, Information Systems, Engineering, Business Analytics, or a related field required; or equivalent combination of education and relevant professional experience.
12+ years of progressive leadership experience in data, analytics, business intelligence, or AI, with at least 5+ years in a senior or executive leadership role
Proven track record of transforming organizations from traditional reporting environments into advanced analytics and AI-driven enterprises
Demonstrated experience designing and implementing modern data platforms (e.g., Microsoft Fabric, Azure, Snowflake, Databricks, or similar)
Strong experience enabling self-service analytics and building scalable semantic models, data products, and governed BI environments
Experience developing and executing data monetization strategies or leveraging analytics to drive measurable revenue growth
Deep understanding of data governance, data quality, master data management, and enterprise data architecture principles
Hands-on experience with advanced analytics, including predictive modeling, prescriptive analytics, and AI/ML applications in business environments
Experience working across complex, multi-business or multi-industry organizations; exposure to BPO, customer experience, marketing services, logistics, or lead generation is highly preferred
Strong commercial acumen with the ability to translate data insights into business value and strategic outcomes Proven ability to lead and scale high-performing, cross-functional teams across data engineering, BI, and data science disciplines Excellent communication and stakeholder management skills, with the ability to influence executive leadership and clearly articulate complex concepts to non-technical audiences Demonstrated success leading organizational change, driving adoption of new technologies, and fostering a data-driven culture Experience integrating data across acquisitions or disparate systems is highly desirable High level of proficiency with modern analytics tools and ecosystems, including Power BI, SQL, and cloud-based data services Strong understanding of security, privacy, and regulatory considerations related to data management (preferably SOC2, PCI & ISO27001) Originally posted on Himalayas
