Engineering - Client Data Engineering - Data Engineer - Analyst - Bengaluru
Goldman Sachs · Bengaluru, Karnataka, India
- On site
- Full-time
- $120,000 / year
- Bengaluru, Karnataka, India
Job highlights
- Design and develop modern data management tools.
- Contribute to an open-source technology platform.
- Collaborate with data consumers and producers.
- Proactively solve data quality issues.
- Work with external data vendors for quality.
About the role
Job Title
Engineering - Client Data Engineering - Data Engineer - Analyst - BengaluruAbout Data Engineering
Data plays a critical role in every facet of the Goldman Sachs business. The Data Engineering group is at the core of that offering, focusing on providing the platform, processes, and governance, for enabling the availability of clean, organized, and impactful data to scale, streamline, and empower our core businesses.
Within Data Engineering, we focus on offering a comprehensive data platform, Legend, which we have made available as an open-source product. Legend includes a full data modeling environment, as well as the execution of data access and controls, and a vast set of value-add products which allow our business users to operate more efficiently.
Leveraging our own Legend offering, our engineers build efficient data solutions that source, curate, and distribute critical data to our businesses, including financial product, pricing, transaction, and client reference data. Our engineers collaborate closely with the business to design and curate business-specific data models, and to transform and distribute data for optimal storage and retrieval.
Who We Look For
Goldman Sachs Engineers are innovators and problem-solvers, building solutions in risk management, big data, mobile and more. We look for creative collaborators who evolve, adapt to change, and thrive in a fast-paced global environment. Are you looking to apply your quantitative skills while deepening your understanding across a vast array of products? Client Data Engineering is a high-value risk management team under Data Engineering Division and is responsible for the governance programs that ensure critical entities modelling and entity data is accurate, complete, and scalable. This data is a critical input and dependency to most trade and client support functions. Client Data Engineering is comprised of four teams, based in Salt Lake City, Bengaluru, Singapore and Sydney.
How You Will Fulfill Your Potential
- Design & develop modern data management tools to curate our most important data sets, models, and processes, while identifying areas for process automation and further efficiencies
- Contribute to an open-source technology - https://github.com/finos/legend
- Engage with data consumers and producers to design appropriate models to suit enable the business
- Proactively solve data quality issues from both tactical and strategic perspectives
- Proactively work with entity data and external vendors (e.g., GLEIF, Factset, Bloomberg, etc..) to ensure we have the highest quality data in our systems
Basic Qualifications
- 1+ years of relevant work experience in a team-focused environment
- In-depth knowledge of relational and columnar SQL databases, including database design
- Proven experience applying domain driven design to build complex business applications
- Deep understanding of multidimensionality of data, data curation and data quality
- Comfort with Agile operating models (practical experience of Scrum / Kanban)
- General knowledge of business processes, data flows and the quantitative models that generate or consume data
- Excellent communications skills and the ability to work with subject matter experts to extract critical business concepts
- Independent thinker, willing to engage, challenge or learn
- Ability to stay commercially focused and to always push for quantifiable commercial impact
- Strong work ethic, a sense of ownership and urgency
- Strong analytical and problem solving skills
- Establish trusted partnerships with key contacts and users across business and engineering teams
- Highly motivated
Preferred Qualifications
- Python
- Financial Services industry experience
- Experience with Pure/Legend
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
© The Goldman Sachs Group, Inc., 2025. 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.
Key skills/competency
- Data Engineering
- Data Management
- SQL Databases
- Domain Driven Design
- Data Curation
- Data Quality
- Agile Methodologies
- Business Processes
- Communication Skills
- Problem Solving
Skills & topics
- Data Engineer
- Data Analyst
- Data Management
- SQL
- Data Curation
- Data Quality
- Agile
- Big Data
- Financial Services
- Bengaluru
How to get hired
- Tailor your resume: Highlight your SQL database, data curation, and Agile experience.
- Showcase your projects: Detail any contributions to open-source or complex data management tools.
- Emphasize problem-solving: Provide examples of how you've improved data quality or processes.
- Prepare for technical interviews: Brush up on SQL, data modeling, and domain-driven design principles.
- Research Goldman Sachs: Understand their commitment to innovation and data-driven solutions.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the primary responsibilities of a Data Engineer Analyst at Goldman Sachs?
- As a Data Engineer Analyst at Goldman Sachs, you will design and develop data management tools, curate data sets, contribute to the open-source Legend platform, engage with stakeholders to design data models, and proactively address data quality issues, working with external data vendors to ensure accuracy.
- What technical skills are essential for this Data Engineer Analyst role at Goldman Sachs?
- Essential technical skills include in-depth knowledge of SQL databases (relational and columnar), database design, domain-driven design, understanding of multidimensional data, data curation, and data quality. Familiarity with Agile methodologies like Scrum or Kanban is also important.
- Does Goldman Sachs value contributions to open-source projects like Legend for this role?
- Yes, contributing to open-source technology like Legend is a key aspect of this role at Goldman Sachs. The job description specifically mentions contributing to the https://github.com/finos/legend project, indicating a strong value placed on open-source engagement.
- What is the role of data quality in the Client Data Engineering team at Goldman Sachs?
- Data quality is paramount. The Client Data Engineering team is responsible for governance programs ensuring critical entity data is accurate, complete, and scalable. You will proactively solve data quality issues and work with external vendors to maintain high data standards.
- What kind of business experience is beneficial for a Data Engineer Analyst at Goldman Sachs?
- General knowledge of business processes, data flows, and quantitative models that generate or consume data is beneficial. The ability to extract critical business concepts and stay commercially focused, pushing for quantifiable commercial impact, is highly valued.
- What is the 'Legend' platform mentioned in the Goldman Sachs Data Engineering description?
- Legend is a comprehensive data platform developed by Goldman Sachs' Data Engineering group, made available as an open-source product. It includes a data modeling environment, data access controls, and value-added products to enhance business user efficiency.
- How does Goldman Sachs approach diversity and inclusion for its engineering roles?
- Goldman Sachs is committed to fostering diversity and inclusion, ensuring every individual has opportunities to grow professionally and personally. They offer training, firmwide networks, and various benefits, and are committed to providing reasonable accommodations for candidates with special needs.