Engineering - Data Platform - Technical Program Manager - Vice President - Dallas

YOUR IMPACT

We are looking for an experienced Technical Program Manager to join our Data Engineering team. Data is the lifeblood of Goldman Sachs, and our data platform is critical in delivering commercial success. In this role, you will partner directly with the leadership of our Data Platform organization to drive the strategy, planning, and execution of the two engines that power data at the firm: our data curation capabilities (data modelling, data APIs, data connections, and SQL query support) and our Lakehouse
, the firm's centralized cloud data store.

This is a hands‑on, technical role at the center of the organization. You will own the roadmap and the commitment book for a large engineering estate, run the risk and controls book of work, steward the financials, support the people agenda, and personally lead the cross‑cutting programs that are too important, too complex, or too cross‑functional to leave to chance. You will spend your days with engineers, architects, and engineering leaders — so you will need enough depth in data and computer science concepts to hold your own in an architecture discussion, read a data model, reason about a query plan, and ask the second and third question, not just the first.

Our open‑sourced Legend Data Platform is central to our strategy; you will help drive its adoption by supporting new workflows and AI‑driven use cases across the firm. Our Lakehouse underpins analytics, reporting, and AI for every division. You will contribute to a team that values customer‑centricity and collaborative development, working alongside Data Engineering leadership, divisional users, and engineers to deliver solutions for internal and external business opportunities — serving a community of 35k+ monthly active users.

Our #1 business principle is "Our clients' interests always come first. Our experience shows that if we serve our clients well, our own success will follow". Every customer is given maximum attention to understand their needs. We adopt the most appropriate approach to drive the business of the customer or institution towards the desired growth. We apply the same approach to the way we build products and deliver customer‑centric, world class products through the collaborative work with our business clients.

The ideal candidate is excited by hard technical problems, comfortable operating with incomplete information, and energized by getting things done. We are looking for a talented and passionate Technical Program Manager who thrives in an extremely entrepreneurial, fast paced environment. This is a high visibility role, backed by some of the senior‑most leaders of the firm, and as such, will require creativity and drive to deliver on an ambitious roadmap.

You will act as a force multiplier for Data Platform leadership — translating strategy into a sequenced plan, making the state of the world visible, unblocking engineering teams, and personally executing on the initiatives that matter most. You will break complex, ambiguous problems into steps that teams can act on, adopting the principles of early releases and incremental delivery to generate evidence of value.

As a Technical Program Manager in Data Engineering, you will:

• Contribute to one of the most critical Engineering functions at Goldman Sachs.

• Own the roadmap — work with engineering leads to define milestones, sequence dependencies, surface trade‑offs, and keep the plan honest as priorities shift.

• Run the commitment book. Maintain a single, trusted view of every major commitment the organization has made — to divisions, to Engineering leadership, to Risk, to Audit, and to regulators — and drive them to closure, escalating early when they are at risk.

• Own the risk book of work. Track and drive remediation of technology risk, control, audit, and regulatory items across the estate; partner with Risk, Compliance, and Engineering leads to ensure obligations are met on time.

• Lead critical cross‑cutting programs end to end. Platform migrations, adoption and decommissioning efforts, data model and API rollouts, query engine and performance initiatives, and AI‑enablement programs —…