As the
Senior Director of Data & Analytics Engineering, you will serve as a senior technology leader responsible for defining and executing the enterprise vision, strategy, and operating model for data and analytics engineering across QTS. You will provide strategic leadership for the architecture, governance, scalability, and modernization of the enterprise data ecosystem, ensuring data becomes a foundational asset that accelerates business growth, operational excellence, and AI-driven innovation.
This role leads multiple teams and technical leaders responsible for building and operating modern, AI-enabled data platforms that power enterprise analytics, business operations, executive decision-making, and future digital capabilities. You will shape long-term data and AI investments, influence enterprise technology strategy, and partner closely with executive leaders across Product, Technology, Finance, Operations, and Business Functions to transform how data is sourced, governed, activated, and consumed across the organization.
As a key leader within the Enterprise Data & Analytics organization, you will establish strategic priorities, develop organizational capability, and champion modern engineering practices that position QTS to scale effectively while maximizing the value of data, analytics, and artificial intelligence.
What You Will Do: (Job Responsibilities) - Define and drive the long-term enterprise vision and strategy for data and analytics engineering, ensuring alignment with corporate growth objectives, digital transformation initiatives, and business strategy.
- Serve as a trusted advisor to executive leadership, influencing enterprise decisions related to data, analytics, AI, governance, and technology investments.
- Establish organizational priorities, operating models, and investment strategies that optimize platform scalability, business value delivery, and technology modernization.
- Lead and develop a multi-layered organization of engineering managers, architects, and technical leaders, building leadership bench strength and succession plans for critical roles.
- Design and evolve the organizational structure, talent strategy, and operating model required to support rapid business growth and emerging technology needs.
- Manage departmental budgets, vendor relationships, and strategic technology investments to ensure effective allocation of resources and achieve business outcomes.
- Drive enterprise-wide adoption of data products, governance standards, AI capabilities, and self-service analytics through partnership with senior business and technology leaders.
- Establish and champion enterprise standards, architectural principles, and data governance frameworks that enable consistency, compliance, and scalability across business functions.
- Represent the Data & Analytics function in executive forums, strategic planning sessions, and enterprise transformation initiatives.
- Other duties as assigned.
- Min. 11 years of experience in data engineering, analytics engineering, or data platform leadership, including 5+ years leading managers or senior technical teams.
- 15+ years of progressive experience in data engineering, analytics engineering, data platforms, or enterprise technology leadership, including 8+ years leading managers, senior leaders, and large-scale engineering organizations.
- Demonstrated success defining and executing enterprise-wide data, analytics, or digital transformation strategies across complex, rapidly scaling organizations.
- Experience leading through multiple layers of leadership, including managers, senior managers, architects, and technical leads.
- Proven ability to influence executive stakeholders and drive alignment across business, product, operations, and technology organizations.
- Experience managing significant budgets, technology investments, vendor relationships, and strategic sourcing decisions.
- Track record of building and scaling high-performing organizations while driving organizational change, capability development, and succession planning.
- Experience presenting technology strategies, business cases, investment recommendations, and transformation roadmaps to executive leadership teams and Board-level audiences.
- Deep expertise in architecting, scaling, and governing modern cloud-based data platforms, including data warehousing, ingestion, transformation, semantic modeling, and data product frameworks, with extensive experience leveraging technologies such as Snowflake, Fivetran, dbt, and contemporary ELT ecosystems.
- Demonstrated expertise in modern streaming and near-real-time data architectures, including Kafka, CDC, and dynamic data processing patterns, with the ability to evaluate, prioritize, and implement solutions that enable business agility and data-driven decision-making.
- Extensive experience with software engineering best practices and agile delivery (sprint planning, code review, testing, CI/CD, on-call, postmortems).
- Strong understanding of enterprise analytics and data consumption strategies, including BI and visualization platforms such as Tableau, Looker, or similar tools, with the ability to influence stakeholders and align analytical capabilities to business objectives.
