Principal TPM: DGX

Intuit's Data, Growth, & Experiences (DGX) organization is building the system of intelligence that powers every AI-driven customer experience across TurboTax, QuickBooks, Credit Karma, and Mailchimp. As a Principal TPM on this team, you will sit at the intersection of enterprise data infrastructure and marketing technology — orchestrating the programs that enable 100M+ customers to experience Intuit as one seamlessly intelligent platform. This is a strategic leadership position for a technical operator who understands data platforms and MarTech ecosystems deeply, moves with urgency, and earns the trust of both engineers and executives. You will drive programs that define how Intuit collects, manages, and activates data to deliver personalised, agentic, done-for-you financial experiences at scale.

Responsibilities

Lead Platform Programs at Enterprise Scale

• Own end-to-end delivery of a portfolio of strategic programs spanning data infrastructure (lakehouse, streaming, IDX), MarTech platforms (CDP, campaign orchestration, personalization), and AI-powered experimentation

• Drive program strategy, architecture alignment, milestone tracking, risk mitigation, and stakeholder communication from initiation through business outcome realization

• Maintain unwavering focus on outcomes — not just delivery milestones — translating engineering execution into measurable business impact

Operate at VP Level with Executive Authority

• Partner directly with VP and Director-level leaders across DGX to shape investment priorities, resolve organizational dependencies, and hold delivery commitments at scale

• Serve as the connective tissue between engineering, product management, data science, marketing, and business stakeholders — enabling decisions that would otherwise stall in silos

• Drive regular executive readouts, program reviews, and async communication that give senior leadership real-time visibility into portfolio health and emerging risks

Build the DGX Program Operating Model

• Define and continuously evolve the TPM frameworks, program health metrics, operating cadences, and delivery standards for the DGX organization

• Establish portfolio visibility practices — dependency maps, risk registers, milestone dashboards — that enable a high say-do ratio across all DGX programs

• Champion Agile and adaptive delivery methodologies, calibrating process rigor to program complexity without adding unnecessary overhead

Champion AI-Native Program Management

• Bring AI tools and agentic workflows into your program management practice — accelerating planning, risk synthesis, stakeholder communication, and decision support

• Collaborate with engineering leads on AI platform programs (e.g., GenOS, agentic pipelines) as a technically fluent partner who can evaluate architectural trade-offs and drive delivery

• Model what it means to be an AI-first builder: demonstrate and teach how LLMs, automation, and intelligent tooling can make the entire team faster and sharper

Develop the TPM Community

• Coach and mentor program managers across DGX, raising the technical and strategic capabilities of the team

• Define best practices, playbooks, and frameworks that scale the TPM discipline and elevate program management standards across the broader Intuit TPM community

• Act as a trusted advisor to product and engineering leaders — someone who is brought in early on hard problems because of the clarity, rigor, and influence you bring

Qualifications

Experience & Track Record

• 12+ years of Technical Program Management experience in large-scale, matrixed technology organizations

• Demonstrated history of delivering enterprise data platform programs — data warehouses, lakehouses, event streaming pipelines, data mesh architectures, or large-scale API platforms

• Direct experience with MarTech ecosystems — CDPs (e.g., Segment, Salesforce, Adobe), campaign orchestration platforms, personalisation engines, A/B experimentation infrastructure, or growth technology

• Proven ability to influence VP- and Director-level stakeholders on strategic investment decisions and organizational priorities

Technical Depth

• Strong conceptual and applied understanding of modern cloud data architectures: data lakehouses (Databricks, Snowflake, BigQuery), event streaming (Kafka, Flink), data mesh or data fabric patterns, and API design

• Fluent in the MarTech stack: understands how CDPs, DMPs, campaign tools, measurement frameworks, and personalization engines interconnect to create unified customer data activation

• Comfortable leading architectural design reviews, evaluating technical trade-offs, and representing engineering complexity in executive narratives

• Conversant in AI/ML concepts as applied to customer data: feature pipelines, model serving, real-time inference, experimentation, and responsible AI practices

Strategic & Analytical Mindset

• Uses data as a first-class tool for program management: monitors leading and lagging indicators, constructs health dashboards, and makes evidence-based course corrections

• Anticipates risks before they materialize; designs mitigation strategies that address root cause, not just symptoms

• Sees across organizational boundaries — identifies systemic dependencies, cross-team sequencing risks, and alignment gaps that others miss

Communication & Influence

• Exceptional written and verbal communicator; able to distill highly technical and complex program status into clear, executive-ready narrative

• Skilled navigator of ambiguity, competing priorities, and organizational tension — influences outcomes without relying on authority

• Builds trust rapidly across engineering, product, data, design, and business functions through credibility, follow-through, and genuine intellectual curiosity

Education

• BS or MS in Computer Science, Engineering, or a related technical discipline — or equivalent practical experience

• PMP, SAFe, or Agile/Scrum certifications are a plus; demonstrated equivalent mastery is equally valued

NICE TO HAVE

• Prior experience at a company with significant MarTech or data platform infrastructure at consumer scale (e.g., Google, Meta, Adobe, Salesforce, Uber, Airbnb, Netflix, Amazon, Intuit)

• Background in financial technology, SaaS, or consumer platforms with 50M+ active users

• Hands-on experience with GenAI application development, LLM platform programs, or agentic AI system delivery

• Familiarity with privacy-by-design frameworks, consent management platforms, or data governance programs at enterprise scale

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit. Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.