AI-Driven Data Engineer for Enterprise Finance Platforms

Goldman Sachs; New York (NY); On-site; USD 130,000 - 200,000; Full time

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 services powering financial planning, expense management, and risk platforms, leveraging AI tools to accelerate development and improve quality.

You will work on enterprise-scale data pipelines and knowledge graphs, collaborating globally with sponsors, users, and engineers while staying current with AI/ML platforms and best practices.

Qualifications

• Bachelor's or master's degree in CS/CE/Data Eng or related field.
• 3+ years using Java, Python to solve data science problems.
• Experience with Pandas, NumPy, PySpark, TensorFlow/PyTorch for scalable pipelines.
• Strong analytical/problem-solving skills with data structures and software design.
• Familiarity with AI tools for software development (LLMs, productivity tools).
• Foundational understanding of AI/agentic systems incl. RAG, prompt engineering.

Responsibilities

• Design, develop, and maintain software and data solutions across the lifecycle.
• Build responsive experiences and robust services powering planning, expense management, and risk platforms.
• Leverage AI tools to accelerate development and improve code quality.
• Build and maintain knowledge graphs and RAG systems for data retrieval.
• Establish governance including logging, explainability, and auditability for AI.

Skills

Java/Python

Data Engineering

AI Tools Familiarity

Analytical Thinking

Ownership & Reviews

Education

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

Tools

Pandas/NumPy

PySpark

TensorFlow/PyTorch

Elasticsearch/OpenSearch

LangChain

AWS

Job description

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 services powering financial planning, expense management, and risk platforms, leveraging AI tools to accelerate development and improve quality.

You will work on enterprise-scale data pipelines and knowledge graphs, collaborating globally with sponsors, users, and engineers while staying current with AI/ML platforms and best practices.