Corporate Planning & Management, Software Engineering, New York, Associate

Goldman Sachs

New York (NY)

On-site

USD 120,000 - 180,000

Full time

14 days+

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Job summary

Goldman Sachs is seeking a Data Engineer in New York to design, develop, and maintain data solutions across the full software lifecycle. You will build scalable data pipelines and robust services powering financial planning, expense management, and risk platforms.

The role requires 3+ years of experience with Java/Python, Pandas/Numpy, PySpark, and familiarity with AI tools. You will collaborate globally and take ownership of features within a dynamic, cloud-native environment.

Qualifications

  • Bachelor's or master's degree in CS, CE, or data engineering.
  • 3+ years of experience with Java and Python to solve data science problems.
  • Experience with Pandas, NumPy, PySpark, TensorFlow/PyTorch for scalable data pipelines and analytics.
  • Strong analytical and problem-solving skills and knowledge of algorithms and data structures.
  • Familiarity with AI tools for software development and LLM-based productivity tools.
  • Foundational understanding of AI, agentic systems, LLMs, prompt engineering, and RAG concepts.
  • Comfortable with technical ownership and working in a global team.

Responsibilities

  • Design, develop, and maintain data solutions across the full software lifecycle.
  • Build scalable data pipelines and robust services powering planning and risk platforms.
  • Leverage AI tools to accelerate development and improve code quality and platform capabilities.
  • Collaborate globally with sponsors, users, and engineers to meet complex requirements.
  • Participate in code reviews to ensure quality and maintainability.
  • Take ownership of features and drive delivery within a global team.

Skills

Java
Python
Pandas/Numpy
PySpark
LLM tools
AI tooling

Education

Bachelor's or Master's in CS/CE/Data Eng

Tools

ElasticSearch
OpenSearch
LangChain
Cloud platforms

Job description

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:
  1. Direct business impact - your work shapes how the firm plans, spends, forecasts, and makes strategic decisions.
  2. Build enterprise-wide solutions that cross data and platform boundaries, and decision-support tools, not just isolated applications.
  3. Cross-functional exposure - partner closely with finance, procurement, product, and risk leaders across a global organization.
  4. 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 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.

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