[Hiring] Vice President, Data Engineering @Tasq Staffing Solutions, Inc.

Role Description

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 unlocks 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
• AI enablement

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
• 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
• Operational forecasting

This leader will work closely with executive stakeholders to ensure that insights are not only generated but operationalized, translating data into measurable business outcomes such as:

• Cost reduction
• Revenue growth
• 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 must possess:

• Deep expertise in modern data platforms (e.g., Microsoft Fabric, Azure, or similar)
• Strong business acumen
• The ability to lead organizational change
• The ability to communicate complex data concepts in a clear and compelling way to both technical and non-technical audiences
• The ability 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.

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).

Requirements

• 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.
• 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.