Technical Program Manager - Data Platform

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.

HOW YOU WILL FULFILL YOUR POTENTIAL

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 — from framing through delivery and measurable outcome.

• Steward the financials. Support leadership on budget planning and forecasting, headcount and vendor spend, and cloud consumption and cost efficiency for the Lakehouse estate; build the reporting that lets leaders make cost decisions with evidence.

• Support the people agenda. Partner with leadership on organizational planning, hiring pipelines, onboarding, location strategy, engagement, and talent and performance processes.

• Go deep technically. Become a proficient user of the Legend platform; understand our data models, data APIs, connection patterns, and query workloads well enough to challenge assumptions, spot dependencies others miss, and represent the platform credibly to senior stakeholders.

• Use data to run the business. Build and maintain the metrics that describe platform health, adoption, delivery throughput, cost, and user experience.

• Partner with AI initiatives. Help ensure new AI-driven capabilities are delivered in line with the firm's data governance and AI standards.

• Establish robust relationships with our divisional partners and users so that what we build lands with impact, and connect the work of the team to the firm's commercial outcomes.

• Improve how the organization runs — sharpen planning, reporting, and governance rhythms, and shape standards within the firmwide Engineering community.

BASIC QUALIFICATIONS

• Bachelor's degree in Computer Science, or a related technical and/or business discipline, or equivalent practical experience

• 7+ years of technical program or project management experience delivering complex engineering programs, ideally within a data, platform, or infrastructure organization

• Working knowledge of data and cloud fundamentals: strong SQL, relational and analytical databases, data modelling concepts, APIs, and public cloud.

• Demonstrated success partnering with engineering teams to deliver technical outcomes — not just tracking them

• Track record of managing dependencies, risks, and issues across multiple teams, and of driving items to closure without direct authority

• Comfortable with Agile ways of working and with the planning and reporting mechanics that support them

• Demonstrated ability to communicate complex technical problems, plans, and trade-offs clearly to both engineers and senior non-technical stakeholders

• Ability to set goals, meet deadlines and effectively communicate progress to stakeholders

• Exceptional organization and attention to detail — you are the person who holds the thread when nobody else does

• Strong analytical and problem-solving skills

• Independent thinker, willing to engage, challenge or learn

• Ability to stay commercially focused and to always push for quantifiable commercial impact

• A healthy obsession with the quality of the platform and the experience of the engineers and users who depend on it, and a willingness to be their internal advocate

• Proven ability to lead by example, with a positive, solutions-oriented attitude

• Strong work ethic, a sense of ownership and urgency

PREFERRED QUALIFICATIONS

• Master's degree or MBA in Computer Science, Engineering, or a related field

• Hands-on exposure to modern Lakehouse and data platform technologies — for example object storage, open table formats (Apache Iceberg, Delta Lake), Spark, Snowflake, Databricks, BigQuery, or comparable

• Familiarity with data modelling and semantic modelling approaches, data APIs, data contracts, and data governance, lineage, and access control concepts

• Understanding of AI and machine learning delivery, including the model development lifecycle, retrieval-augmented generation and LLM-based applications, and the data foundations required to support them

• Scripting or data manipulation skills in Python

• Experience supporting a technology risk, controls, audit, or regulatory book of work

• Prior experience in financial services or another highly regulated, data-intensive environment

• Experience with, or contributions to, open source data tooling — our Legend platform is open sourced through FINOS

WHO YOU ARE

We care as much about how you work as what you have worked on. You will thrive here if you are:

• Self-motivated and driven — you set your own pace and do not need to be told what needs doing next.

• Intellectually curious — you pick up new technical domains quickly, and you enjoy the learning as much as the outcome.

• Someone who looks around corners — you anticipate the problem three months out and start solving for it now.

• Detail-oriented and organized — nothing falls through the cracks on your watch.

• Execution- and outcome-oriented — you can point to what measurably improved because you were there.

• A pragmatist — you know when 80% delivered this week beats 100% delivered next quarter, and you can tell the difference.

• An incremental deliverer — you put work in front of people early, invite the feedback, and iterate.

• A strong communicator, in writing and in the room, with engineers and with senior leadership alike.

• Collaborative and genuinely helpful to engineers — you understand how they work, you make their lives easier, and you earn their trust through substance.

• Commercially aware — you can connect your work to the firm's goals and articulate why it matters.

• Flexible and happy to wear many hats — the mix of roadmap, risk, financials, people, and delivery will shift week to week.

• Comfortable with ambiguity — you can make progress when the problem is not yet fully defined.

ABOUT GOLDMAN SACHS

ENGINEERING – At Goldman Sachs, our Engineers don't just make things – we make things possible. Change the world by connecting people and capital with ideas. Solve the most challenging and pressing engineering problems for our clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity at the speed of market.