OUR IMPACT
Corporate Planning & Management (CPM) unifies Finance & Planning, Global Procurement, Product & Reporting and CPM Engineering teams to deliver business planning and analytics, expense management, third party risk management, sustainability strategy for our operations and supply chain, and governance strategies across the firm.
CPM Engineering provides engineering solutions that enable the firm to manage third-party spend & risk management, plan budgets, forecast financial scenarios, allocate expenses and support corporate decision making in-line with the firm’s strategic objectives.
Why does this role stand out:
- Direct business impact - your work shapes how the firm plans, spends, forecasts, and makes strategic decisions.
- Build enterprise-wide solutions that cross data and platform boundaries, and decision-support tools, not just isolated applications.
- Cross-functional exposure - partner closely with finance, procurement, product, and risk leaders across a global organization.
- Complex, meaningful problems - work on systems that improve transparency, controls, efficiency, and scalability across enterprise operations.
We offer:
- The opportunity to work on high-impact platforms that directly influence firm-wide financial planning and operational resilience
- Access to modern cloud-native architectures, modern AI driven developer productivity tools (Copilot, Claude Code etc), distributed systems, and large-scale data pipelines
- A forward-looking environment where AI tools, agentic frameworks, and intelligent automation are actively shaping the next generation of our solutions
- A collaborative, global team where you can learn from experts and grow your career
HOW YOU WILL FULFILL YOUR POTENTIAL
As a Data Engineer on our team, you will:
- Design, develop, and maintain software and data solutions across the entire software lifecycle from requirements gathering and architecture through implementation, testing and deployment
- Build responsive, intuitive experiences and robust services that power financial planning, expense management, and risk platforms
- Leverage AI tools and techniques (e.g., code-generation assistants, LLM-powered automation, prompt engineering, Spec-Driven Development) to accelerate development, improve code quality, and enhance platform capabilities
- Build and maintain knowledge graph and RAG systems to enable document and data retrieval, querying and searching
- Establish robust governance frameworks including logging, explainability, and auditability to ensure AI quality and reliability
- Collaborate globally with sponsors, users, and engineering colleagues across multiple divisions to create end-to-end solutions that meet complex business requirements
- Participate in code reviews to ensure quality, maintainability, and adherence to engineering best practices
- Take technical ownership of features and components, managing multiple stakeholders and driving delivery within a global team
- Stay current with the latest advancements in AI/ML platforms, tools, and software engineering practices to continuously improve our solutions
QUALIFICATIONS
Required
- Bachelor's or master's degree in Computer Science, Computer Engineering, Data Engineering or a similar field of study.
- 3+ years of proficiency in using programming languages (Java, Python etc) to solve data science problems.
- Data Science & Engineering — experience using industry-standard libraries (e.g., Pandas, NumPy, PySpark, TensorFlow/PyTorch) to build scalable data pipelines, perform data modeling, and enable enterprise insights on large, complex datasets.
- Strong analytical and problem-solving skills - experience with algorithms, data structures, and software design
- Familiarity in utilizing AI tools for software development (e.g., AI-assisted coding, code review tools, LLM-based productivity tools)
- Foundational understanding of AI and agentic systems - familiarity with concepts such as large language models, prompt engineering, retrieval-augmented generation (RAG) etc.
- Comfortable with technical ownership, managing multiple stakeholders, and working as part of a global team
Preferred - Experience That Can Set You Apart
- GenAI & Intelligent Data Retrieval using vector databases, embedding models, and agentic frameworks (e.g., LangChain) — to enable intelligent querying and synthesis of insights across large enterprise data assets.
- Experience with Distributed Databases & Search Platforms— building and optimizing scalable, distributed data systems (e.g ElasticSearch, OpenSearch) with a focus on indexing, query performance, and real-time data retrieval; familiarity with search relevance tuning, vectors and embeddings across large datasets.
- Advanced Data Analytics & Data Science experience applying data science methodologies — including statistical analysis, predictive modeling, and knowledge graphs — across diverse data types.
- Familiarity with MLOps practices including CI/CD for ML, model deployment, and monitoring
- Knowledge of cloud-native solutions (preferably AWS)
- Knowledge of the financial industry - corporate planning, expense management, or risk functions
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 several 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.
© The Goldman Sachs Group, Inc., 2023. All rights reserved.
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.
Skills Required
- Bachelor's or master's degree in Computer Science, Computer Engineering, Data Engineering or similar
- 3+ years proficiency in programming languages (Java, Python etc.)
- Experience using data libraries and frameworks (Pandas, NumPy, PySpark, TensorFlow/PyTorch) to build scalable data pipelines and models
- Strong analytical and problem-solving skills with experience in algorithms, data structures, and software design
- Familiarity with AI-assisted development tools and LLM-based productivity tools
- Foundational understanding of AI and agentic systems (LLMs, prompt engineering, RAG)
- Comfortable taking technical ownership, managing multiple stakeholders, and working on global teams
- GenAI, vector databases, embedding models, LangChain or similar
- Experience with distributed databases and search platforms (ElasticSearch, OpenSearch)
- Advanced data analytics, predictive modeling, knowledge graph experience
- Familiarity with MLOps practices including CI/CD for ML, deployment and monitoring
- Knowledge of cloud-native solutions (preferably AWS)
- Knowledge of financial industry corporate planning, expense management, or risk functions
Goldman Sachs Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Goldman Sachs and has not been reviewed or approved by Goldman Sachs.
-
Healthcare Strength — Coverage includes medical, dental, vision, disability, life and accident insurance, with multiple plan options and most premiums subsidized; coverage often starts on day one. Wellness resources, on-site health centers in some locations, and EAP access reinforce the depth of health support.
-
Parental & Family Support — Family care includes on-site childcare in some offices, expectant parent resources, and transitional programs for returning parents. Feedback suggests parental leave is very generous, with reports of around 20 weeks paid leave and stipends for adoption, surrogacy, and fertility-related services.
-
Retirement Support — The firm provides a 401(k) plan with employer matching contributions and broad financial education to help employees plan for retirement. Resources also support saving for education and preparing for unexpected events.
Goldman Sachs Insights
What We Do
At Goldman Sachs, we believe progress is everyone’s business. That’s why we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, Goldman Sachs is a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices in all major financial centers around the world. More about our company can be found at www.goldmansachs.com








