Department OverviewThe Data & Analytics team enables data-driven decision making across the enterprise by delivering scalable data platforms, advanced analytics capabilities, AI/ML foundations, and trusted data products. We empower business and technology teams with modern data infrastructure, governance, and engineering practices to transform data into actionable insights and business value.
Position SummaryWe are seeking a
Senior Director, Platform Engineering, to lead the vision, strategy, and execution of the enterprise Data & Analytics platform engineering function. This leader will be responsible for building and evolving the foundational platforms, tools, automation, and reliability practices that power data engineering, analytics, artificial intelligence, machine learning, and data product delivery across the organization.
The Senior Director will oversee teams responsible for cloud-native data platforms, developer experience, platform operations, DevOps, Site Reliability Engineering (SRE), observability, security integration, and infrastructure automation. This leader will drive modernization efforts, establish scalable engineering standards, and ensure the Data & Analytics ecosystem delivers secure, reliable, and highly available services that support both current and future business needs.
This role partners closely with Data Engineering, Analytics, Data Science, AI/ML, Architecture, Cybersecurity, Infrastructure, Product Management, and business stakeholders to define platform strategy, optimize delivery velocity, and maintain operational excellence across the enterprise data landscape.
DutiesPlatform Strategy & Leadership- Define and execute the long-term Platform Engineering strategy for the Data & Analytics organization, aligning investments with enterprise technology and business objectives.
- Ensure data platform capabilities directly align with and empower core business outcomes, particularly in consumer-facing digital channels and complex global supply chain domains.
- Establish a modern, scalable, and standardized platform engineering capability that accelerates data product delivery while ensuring operational reliability, security, and compliance.
Data Platform Engineering & Modernization- Lead the evolution of enterprise data platform capabilities supporting data ingestion, transformation, storage, governance, AI/ML workloads, analytics, and real-time processing.
- Champion a formal Cloud FinOps culture for data platforms, proactively forecasting, monitoring, and optimizing compute and storage costs at extreme scale across cloud environments.
- Drive modernization of CI/CD, DataOps, MLOps, and Infrastructure as Code (IaC) capabilities to improve engineering efficiency and delivery quality.
Reliability, Security & Operations- Establish enterprise-grade Site Reliability Engineering (SRE) practices for data and analytics platforms.
- Define service-level objectives (SLOs), reliability metrics, operational standards, and incident management practices across the platform ecosystem.
Engineering Excellence & Innovation- Drive adoption of DataOps, DevOps, platform engineering, and automation best practices throughout the organization.
- Evaluate emerging technologies and industry trends to continuously improve platform capabilities and developer productivity.
- Establish engineering standards, architectural guardrails, and technical governance processes that support sustainable growth and innovation.
Stakeholder & Vendor Management- Serve as the executive technology partner for Data & Analytics, Infrastructure, Security, Architecture, and Product leadership teams.
- Build strong relationships with strategic vendors, cloud providers, and technology partners.
- Provide executive-level communication and reporting on platform health, engineering investments, technology risks, and strategic outcomes.
Talent Leadership- Attract, develop, and retain high-performing engineering leaders and technical talent.
- Build organizational capabilities through coaching, mentoring, succession planning, and leadership development.
- Foster an inclusive, collaborative, and performance-driven culture that encourages accountability, ownership, and continuous learning.
Qualifications- Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field; Master's degree preferred.
- 15+ years of progressive experience in software engineering, platform engineering, infrastructure engineering, cloud technologies, data platforms, or related disciplines.
- 8+ years of experience leading large-scale engineering organizations, including managers and senior technical leaders.
- Proven experience defining and executing enterprise platform strategies in cloud-native environments, including large-scale cloud cost management (FinOps).
- Deep expertise in Platform Engineering, DevOps, DataOps, SRE, cloud infrastructure, automation, and modern software delivery practices.
- Experience building and operating large-scale data and analytics platforms supporting enterprise data products, AI/ML solutions, and critical business workloads.
- Demonstrated success leading platform modernization, cloud transformation, and engineering standardization initiatives.
- Strong executive presence with the ability to influence senior business and technology leaders.
- Experience managing large-scale operational environments with accountability for reliability, availability, security, and performance outcomes.
- Exceptional communication, organizational, and stakeholder management capabilities.
- Proven ability to lead through complexity, ambiguity, organizational change, and rapid growth.
Preferred Qualifications- Advanced degree in Computer Science, Engineering, Business Administration, or a related field.
- Deep experience with cloud ecosystems including AWS, Google Cloud Platform (GCP), and/or Microsoft Azure.
- Expertise in Infrastructure as Code, Kubernetes, container platforms, CI/CD, DataOps, MLOps, and platform automation frameworks.
- Experience supporting modern data architectures such as data lakes, streaming platforms, data mesh, and AI/ML platforms tailored for consumer, restaurant, or supply chain domains.
- Strong understanding of data governance, regulatory compliance, data security, privacy, and enterprise data management practices.
- Experience implementing enterprise observability, operational intelligence, and reliability engineering frameworks at scale.
- Background leading global engineering organizations supporting mission-critical data and analytics capabilities.
CompensationBonus Eligible: Yes
Long - Term Incentive: Yes
Benefits Eligible: Yes
Salary RangeThe expected salary range for this role is $237,102 - $296,377 per year
The above represents the expected salary range for this job requisition. Ultimately, in determining your pay, we may also consider your experience, and other job-related factors.
Additional Information: Benefits eligible: This position offers health and welfare benefits, including but not limited to comprehensive health insurance, which includes medical, prescription drug, mental health, dental and vision coverage, as well as, life insurance.
