Software Engineering - Data, Lakehouse and AI Data Platform Engineer-Bangalore-Associate
Goldman Sachs · Posted Oct 30
Investment banking, securities, asset management, and wealth management services
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About the role
Goldman Sachs engineering teams build scalable systems and turn data into action, with this role sitting in the Lakehouse and AI Data Platform team. The team delivers data models, pipelines and platform capabilities that support analytics, operational decision-making and emerging AI use cases. The Data Engineer will design, build, test and support production data pipelines and curated datasets, and may contribute shared tooling or framework components where platform functionality gaps exist.
What you will do
- Build, enhance and support batch and streaming data pipelines on the Lakehouse and AI data platform.
- Refactor or modernise existing data flows where needed to improve reliability, performance and maintainability.
- Where needed, build reusable tooling to improve delivery, consistency and operational support.
- Ensure data pipelines are production-ready, well tested and operationally supportable.
- Develop raw, refined and curated datasets that support analytics, reporting and AI use cases.
- Apply sound data modelling principles to represent business entities, relationships and historical change accurately.
- Work with consumers to shape data products that are usable, well documented and aligned to business needs.
- Implement controls to validate completeness, accuracy and consistency of data across pipelines and datasets.
- Use reconciliation approaches to build confidence in production outputs and investigate breaks where they arise.
- Contribute to clear standards for testing, monitoring and issue resolution.
- Contribute to practical improvements in testing, monitoring or reconciliation tooling where these strengthen platform reliability and day-to-day delivery.
Skills used in this role
What the employer is looking for
- 3+ years of experience
- Bachelor’s or master’s degree in a relevant discipline, or equivalent practical experience, with evidence of strong quantitative skills or data engineering expertise.
- Strong hands-on programming experience in Python or Java.
- Good working knowledge of SQL, including troubleshooting, optimization and data analysis.
- Ability to learn new tools, internal platforms and delivery workflows quickly.
- Familiarity with software engineering fundamentals, including version control, testing, release discipline and CI/CD practices.
- Understanding of temporal data modelling, including the handling of historical state and change over time.
- Knowledge of schema design, schema evolution and data compatibility considerations.
- Understanding of partitioning, clustering and other techniques used to improve data performance at scale.
- Ability to make sensible design choices across normalized and denormalized models, and between natural and surrogate keys.
- Practical approach to data quality, reconciliation and root-cause analysis.
- Experience building or supporting production data pipelines in a collaborative engineering environment.
- Experience working with distributed data processing frameworks such as Apache Spark.
- Working knowledge of common data formats such as JSON, Avro and Parquet.
- Stronger ownership of technical design across multiple datasets or pipeline domains.
- Experience guiding implementation standards, code quality and engineering practices within a team.
- Ability to lead delivery for a workstream, manage dependencies and support less experienced engineers.
- sound judgement in technical trade-offs
- attention to detail in data correctness and testing
- a clear and structured approach to problem solving
- willingness to work closely with stakeholders and partner teams
- an interest in developing long-term expertise within the firm
Benefits and support
- Compensation and benefits are detailed in the job posting
About Goldman Sachs
The Goldman Sachs Group, Inc. is a leading global financial institution that delivers a broad range of financial services across investment banking, securities, investment management, and consumer banking to a diverse client base. Established in 1869 and headquartered in New York City, the firm serves corporations, financial institutions, governments, and high-net-worth individuals worldwide.
- Industry
- Investment Banking
- Company size
- 47400+ employees
- Founded
- 1869
- Location
- New York, New York, USA
- Funding stage
- Public Company
Leadership
Chairman and Chief Executive Officer
President and Chief Operating Officer
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