Senior Director, Technology Program Management

Salesforce•San Francisco, CA

1d•Hybrid

About The Position

Salesforce is seeking an exceptional Senior Director of Technology Program Management to serve as the execution backbone for the Chief Data Officer’s organization. This leader will own portfolio governance and execution across our most strategic Data/AI ML Platforms, Analytics, AI, Integration, Automation, Governance, and platform transformation initiatives. The role requires a rare combination of deep technical fluency, exceptional program rigor, executive presence, and the courage to drive accountability across organizational boundaries. This is not a traditional PMO role. We are looking for a technology leader who can operate at executive altitude while going deep enough to understand architecture, data flows, technical dependencies, product constraints, operational readiness, and delivery risk. This person will create clarity where there is ambiguity, surface issues early, drive decisions, and ensure that commitments translate into measurable outcomes.

Requirements

12–15+ years of experience in technical program management, engineering, product/platform delivery, or related technology leadership roles, including significant experience at enterprise scale.
Proven track record leading portfolios of complex, multi-year Data, Analytics, Cloud, Platform, or AI programs with substantial technical and organizational interdependencies.
Technically credible with senior engineers and architects and can understand, question, and challenge complex system designs without needing to be the primary architect.
Strong knowledge of modern data architectures, distributed/cloud data platforms, software development lifecycles, APIs/integration, data governance, reliability, security, and AI/agent architectures.
Exceptional executive communication, structured problem solving, financial and capacity management, and the ability to turn ambiguity into clear decisions and executable plans.
Comfortable challenging senior stakeholders respectfully, holding peers and teams accountable, and making difficult calls when commitments or outcomes are at risk.
Experience building and developing high-performing TPM or portfolio teams and leading effectively in a global, matrixed organization.
Hands-on and credible with AI: you do not simply sponsor AI transformation—you use it, learn it, and model how it should change the way technology teams work.
Direct experience delivering enterprise-scale customer, master, reference, or operational data platforms; analytics/BI; data governance; integration platforms; or production AI/agent capabilities.
Experience with large SaaS environments such as Salesforce, cloud data platforms (Data 360/Snowflake/Databricks etc), data observability, metadata/semantic layers, and enterprise platform modernization.
Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical discipline.

Nice To Haves

An advanced degree is a plus.

Responsibilities

Own the end-to-end portfolio operating model for the Chief Data & Intelligence Office, connecting strategy, investments, roadmaps, milestones, dependencies, capacity, risks, and measurable business outcomes.
Establish a single, trusted view of portfolio health: what is on track, what is at risk, why it is at risk, who owns recovery, and what decisions or executive interventions are required.
Drive annual and quarterly planning, prioritization, sequencing, resource trade-offs, portfolio reviews, and executive steering mechanisms across a highly interdependent technology landscape.
Define portfolio health metrics and mechanisms that improve delivery predictability, decision velocity, dependency management, and value realization.
Lead large-scale, technically complex Data & AI programs spanning modern data platforms, data engineering and ingestion, analytics, governance, master/reference data, integration and APIs, cloud infrastructure, AI/ML, generative AI, agents, and enterprise automation.
Partner deeply with Product, Engineering, Architecture, Security, Operations, Governance, and business leaders to translate technical roadmaps into executable integrated plans.
Understand and challenge architecture, sequencing, non-functional requirements, technical debt, security, reliability, scalability, data quality, and production-readiness assumptions; identify systemic risks before they become delivery failures.
Manage critical cross-program and cross-platform dependencies, including dependencies across Data Solutions, other Digital Enterprise Technology pillars, Technology & Product, business teams, and strategic partners.
Create a culture where commitments mean something. Establish clear owners, dates, decision rights, exit criteria, and measurable outcomes—and hold yourself and others equally accountable.
Surface risks and uncomfortable truths early. Constructively call out missed commitments, insufficient ownership, slow decisions, or execution gaps, and drive a credible recovery plan.
Lead high-cadence operating reviews and technical deep dives that remove blockers, accelerate decisions, and keep business-critical milestones on track.
Balance inclusion with accountability: invite diverse perspectives, build trust, and create psychological safety while maintaining a high bar for performance, transparency, and follow-through.
Influence without authority across senior leaders and globally distributed teams; resolve competing priorities and drive alignment when ownership spans multiple organizations.
Serve as a trusted advisor to VP/SVP executives, translating complex technical and execution signals into concise insights, choices, risks, and recommendations.
Reduce organizational friction by clarifying ownership, resolving dependency conflicts, and ensuring teams understand how their commitments affect the broader portfolio.
Be a visible role model for AI-first ways of working. Personally use AI and automation to improve planning, synthesis, dependency analysis, risk detection, executive reporting, decision support, and program operations.
Bring practical fluency in generative AI, LLMs, agents, agentic workflows, RAG, embeddings/vector search, context engineering, tool orchestration, evaluation, observability, AI governance, and responsible AI.
Challenge the TPM organization to automate coordination work, codify reusable AI skills and workflows, and demonstrate measurable gains in speed, quality, and capacity.
Partner with technical teams to ensure AI programs are grounded in trusted data, governed context, secure access, measurable quality, and production-grade operational controls.
Build, mentor, and scale a high-performing portfolio and Technical Program Management organization; develop leaders who combine technical depth with disciplined execution.
Set a high bar for program craftsmanship, executive communication, judgment, ownership, and continuous improvement.
Create an inclusive, transparent culture where teams debate constructively, escalate responsibly, learn quickly, and remain relentlessly focused on outcomes.