Data Governance at Goldman Sachs is being reinvented.
This is a chance to define and build the next generation of Data Governance infrastructure for Global Banking & Markets. Our team owns the Data Governance strategy across a truly global platform spanning New York, London, Warsaw, Bengaluru, Singapore, Dallas, and Hyderabad, supporting regulators, data consumers, and business stakeholders around the world.
This is not a traditional governance technology role. We are not treating governance as a bolt-on control layer, a manual parallel process, or an afterthought audit trail. We are embedding governance intelligence directly into platform and product design from day one: governance by design, not governance by exception.
As part of the firmwide One GS 3.0 transformation, we are modernizing to cloud-native architecture and building an AI-first data governance capability where engineering, controls, and business workflows converge. The mission is bold: automate operational toil, interpret an ever-changing legal and regulatory landscape, detect issues before they surface, and create proactive monitoring that scales with global market complexity.
We are looking for disruptors, builders, and systems thinkers who want to reimagine what data governance can be: an integrated, automated, self-improving, evergreen solution where governance enables data-driven transformation rather than restricting it.
How will you fulfil your potential?
- Build secure, high-quality, maintainable systems with technology and strategy teams using approved tools and modern engineering practices.
- Partner with global technology and business teams to deliver regulatory obligations as integrated platform capabilities.
- Design AI-enabled workflows that automate exception handling, reduce manual reconciliation, and improve control transparency.
- Embed intelligence directly into the systems themselves so they can detect anomalies, route exceptions, explain decisions, and support proactive monitoring.
- Build AI-powered governance capabilities that continuously interpret global regulatory requirements, internal standards, and policy updates for evergreen compliance coverage.
- Engineer governance-by-design controls into data pipelines and data products, including policy-aware lineage, ownership, and quality enforcement.
- Help move the team from reactive compliance to regulatory-by-design engineering.
- Track key performance metrics to measure control effectiveness, operational efficiency, and transformation outcomes.
- Learn from and contribute to engineers building the next generation of cloud and AI systems for markets infrastructure.
Responsibilities
- Lead technical discussions, architecture, design, development, and testing for strategic regulatory engineering initiatives.
- Define and enforce engineering best practices across the delivery lifecycle.
- Guide teams in building reliable, scalable, secure, and auditable systems.
- Drive the shift toward AI-first, embedded, and explainable regulatory platforms.
- Help create systems that make regulatory outcomes faster, smarter, and more transparent.
Experience
- 8+ years of experience designing and implementing real-time distributed processing systems and event-driven architectures.
- Proven expertise in large-scale migrations from on-premises legacy systems to cloud-based Lakehouse environments, preferably AWS.
- Strong understanding of cloud architecture, managed services, and containerization such as Docker and Kubernetes.
- Experience building secure, highly available, scalable systems in large enterprise environments.
- Proficiency in Python, C++, or Java.
- Experience developing, testing, and maintaining production-grade code.
- Experience building AI-first applications and interfaces with generative features, streaming LLM responses, and Model Context Protocol integrations.
- Practical experience using AI/ML to drive operational automation, transparency, anomaly detection, and proactive monitoring.
Relevant
- Hands-on experience with Databricks and Snowflake in enterprise Lakehouse patterns, including governed data product development and operationalized controls.
- Practical experience designing interconnected graph ecosystems for advanced data asset governance, including lineage intelligence, ownership relationships, and policy propagation.
- Experience with near real-time transactional systems and NoSQL/event platforms such as Kafka and Elasticsearch.
- Bachelor’s degree in computer science, engineering, or a related field, or equivalent practical experience.
- Experience as an Engineering Manager or Senior Technical Lead, ideally in cloud-native development or platform engineering.
- Experience designing multi-agent systems using frameworks with governed orchestration logic.
- Strong product mindset and the ability to redefine how regulatory outcomes are delivered at scale.
ABOUT GOLDMAN SACHS
At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.
We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers.
We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html
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Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law