The Data Platform Engineering leader is accountable for the strategy, engineering, delivery, reliability, adoption, and continuous evolution of the TIAA's enterprise data platform and its foundational capabilities.
This executive will lead a global organization of 100+ employees and strategic partners responsible for creating a secure, governed, resilient, and self-service data platform that enables enterprise and federated teams to rapidly build, operate, discover, and consume trusted data products and AI-enabled solutions. The role will oversee the platform engineering across platform solutions, data engineering tools and reliability, governance/security/privacy enablement, developer and business user experience, and AI-enabled platform engineering. The leader will establish clear capability ownership and drive the organization towards a scalable, capability and product-based platform model.
Key Responsibilities and Duties Platform Strategy & Roadmap Own the target-state architecture, engineering strategy, and multi-year roadmap for the enterprise data platform, aligning investments to business, Data, Analytics, Governance and AI priorities.
Platform Engineering & Modernization Deliver scalable, modular, cloud-native platform capabilities and reusable engineering patterns that simplify architecture, reduce duplication, accelerate data-product delivery, and enable platform as a service for federated teams.
Governance, Security, Quality & Privacy by DesignPartner with Data Governance, Cybersecurity, Privacy, Risk, and Architecture to translate enterprise policies into automated, reusable platform controls covering access, quality, metadata, lineage, classification, privacy, and policy enforcement.
Reliability & Engineering ExcellenceEstablish engineering standards and automation across observability, infrastructure-as-code, CI/CD, testing, release management, resiliency, incident management, performance, and repeatable platform operations.
Developer & Business Experience Drive adoption of self-service capabilities, the Enterprise Data Portal, data-product discovery, developer tooling, federation & onboarding, and common platform patterns that improve productivity and reduce friction for data producers and consumers.
AI-Enabled Engineering & Platform Innovation Apply AI and GenAI across data engineering, governance, platform operations, developer experience, and the software development lifecycle while ensuring the platform provides the trusted data, metadata, semantic context, and services required for enterprise AI at scale.
Organizational Leadership & Talent Lead and develop a high-performing global organization. Build a strong leadership bench, strengthen succession, grow critical engineering capabilities, and optimize the balance of internal talent and external partners.
Portfolio, Vendor & Platform Economics Own investment prioritization, workforce strategy, vendor partnerships, technology rationalization, and platform economics while ensuring major initiatives are delivered with appropriate cost, quality, risk, and business outcomes.
Executive Partnership & Influence Represent Data Platform Engineering in senior leadership forums, translating complex technology choices into business implications, investment decisions, risk trade-offs, and measurable enterprise outcomes.
Operations & Production Support Provides Tier 2 and Tier 3 engineering support, ensuring effective 24x7x365 support for assigned technology, including managing vendor escalations to resolve production issues and minimize business impact.
Educational Requirements- University (Degree) Preferred
Work ExperiencePhysical Requirements- Physical Requirements: Sedentary Work
Career Level 11PL
POSITION SUMMARY:The Managing Director - Data Platform Engineering is accountable for the strategy, engineering, delivery, reliability, adoption, and continuous evolution of the TIAA's enterprise data platform and its foundational capabilities.
This executive will lead a global organization of 100+ employees and strategic partners responsible for creating a secure, governed, resilient, and self-service data platform that enables enterprise and federated teams to rapidly build, operate, discover, and consume trusted data products and AI-enabled solutions. The role will oversee the platform engineering across platform solutions, data engineering tools and reliability, governance/security/privacy enablement, developer and business user experience, and AI-enabled platform engineering. The leader will establish clear capability ownership and drive the organization towards a scalable, capability and product-based platform model.
This leader will partner closely with Enterprise Architecture, Cybersecurity, Data Governance, Privacy, Risk, Infrastructure, AI/ML business & technology organizations, and federated data teams to establish enterprise standards and make them easy to consume through reusable engineering patterns, automation, self-service capabilities, and policy driven controls.
The role combines hands-on technical depth with strategic portfolio oversight, ensuring delivery excellence, 24x7x365 operational resilience, regulatory compliance, and innovation aligned with firm standards.
KEY RESPONSIBILITIES: Platform Strategy & Roadmap Own the target-state architecture, engineering strategy, and multi-year roadmap for the enterprise data platform, aligning investments to business, Data, Analytics, Governance and AI priorities.
Platform Engineering & Modernization Deliver scalable, modular, cloud-native platform capabilities and reusable engineering patterns that simplify architecture, reduce duplication, accelerate data-product delivery, and enable platform as a service for federated teams.
Governance, Security, Quality & Privacy by Design Partner with Data Governance, Cybersecurity, Privacy, Risk, and Architecture to translate enterprise policies into automated, reusable platform controls covering access, quality, metadata, lineage, classification, privacy, and policy enforcement.
Reliability & Engineering Excellence Establish engineering standards and automation across observability, infrastructure-as-code, CI/CD, testing, release management, resiliency, incident management, performance, and repeatable platform operations.
Developer & Business Experience Drive adoption of self-service capabilities, the Enterprise Data Portal, data-product discovery, developer tooling, federation & onboarding, and common platform patterns that improve productivity and reduce friction for data producers and consumers.
AI-Enabled Engineering & Platform Innovation Apply AI and GenAI across data engineering, governance, platform operations, developer experience, and the software development lifecycle while ensuring the platform provides the trusted data, metadata, semantic context, and services required for enterprise AI at scale
. Organizational Leadership & Talent Lead and develop a high-performing global organization of 100+ employees and strategic partners. Build a strong leadership bench, strengthen succession, grow critical engineering capabilities, and optimize the balance of internal talent and external partners.
Portfolio, Vendor & Platform Economics Own investment prioritization, workforce strategy, vendor partnerships, technology rationalization, and platform economics while ensuring major initiatives are delivered with appropriate cost, quality, risk, and business outcomes.
Executive Partnership & Influence Represent Data Platform Engineering in senior leadership forums, translating complex technology choices into business implications, investment decisions, risk trade-offs, and measurable enterprise outcomes.
Operations & Production Support Provides Tier 2 and Tier 3 engineering support, ensuring effective 24x7x365 support for assigned technology, including managing vendor escalations to resolve production issues and minimize business impact.
REQUIRED QUALIFICATIONS:- 10+ years of technology and data platform engineering experience
- 10+ years of experience as a senior technology leader, leading large, globally distributed engineering organizations
- 3+ years of AWS recent experience
- 3+ years of Snowflake recent experience
- Data governance experience
PREFERRED QUALIFICATIONS:- 12+ years of technology and data platform engineering experience
- Financial services industry experience
- University degree - Computer Science, Engineering, or a related technical discipline; advanced degree & certification(s) are a plus
- Demonstrated success building high-performing teams across employees, contractors, and strategic partners
- Strong stakeholder management skills, with demonstrated ability to collaborate across Technology, Architecture, Security, Risk, Business, and senior leadership to drive delivery excellence, organizational change, and innovation aligned with firm standards.
- Proven experience defining and executing enterprise-scale data platform strategies, modernization programs, and technology transformations within large, complex organizations. Financial services or another highly regulated industry strongly preferred.
- Strong technical understanding of cloud-native data architectures, modern data platforms, data products, distributed processing, enterprise integration, metadata, semantic layers, and modern data consumption patterns.
- Strong understanding of platform engineering, infrastructure-as-code, DevSecOps, CI/CD, observability, reliability engineering, resiliency, automation, and enterprise production operations.
- Demonstrated building and operationalization of AI, GenAI, and agentic technologies and their application across data engineering, platform operations, governance, developer productivity, and enterprise data consumption.
- Demonstrated ability to operate technology platforms as enterprise products, with strong focus on customer experience, self-service, adoption, engineering productivity, reliability, and measurable business outcomes.
- Strong understanding of cybersecurity, privacy, data governance, regulatory requirements, risk management, resiliency, and controls required to operate enterprise data platforms in a highly regulated environment. Experience in data governance tool engineering strongly preferred.
- Demonstrated ability to influence and collaborate across senior business and technology leadership, Enterprise Architecture, Cybersecurity, Risk, Data Governance, Infrastructure, AI, and federated engineering organizations.
- Proven ability to simplify complex technology environments and operating models, establish clear accountability, modernize engineering practices, and deliver measurable improvements in speed, quality, reliability, adoption, and cost.
Related Skills
Application Programming Interface (API) Development/Integration, Automation, Communication, Consultative Communication, Containerization, DevOps, Enterprise Application Integration, Influence, Organizational Savviness, Problem Solving, Prototyping, Relationship Management, Scalability/Reliability, Software Development Life Cycle, Systems Design/Analysis
Anticipated Posting End Date:2026-09-10
Base Pay Range: $195,000/yr - $308,000/yr
Actual base salary may vary based upon, but not limited to, relevant experience, time in role, base salary of internal peers, prior performance, business sector, and geographic location. In addition to base salary, the competitive compensation package may include, depending on the role, participation in an incentive program linked to performance (for example, annual discretionary incentive programs, non-annual sales incentive plans, or other non-annual incentive plans).
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