Goldman Sachs
Software Engineer
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Job Description
At Goldman Sachs, engineering teams are positioned at the center of the business, building scalable systems, solving complex technical problems and turning data into action. In data engineering roles, the emphasis is on designing, building and maintaining large-scale data platforms, delivering production pipelines, improving reliability and quality, and partnering closely with users of the platform.
This is a delivery-focused role for engineers who want to build robust data assets in production, work with modern data technologies, and grow over time within the firm. You will contribute to the data models, pipelines and platform capabilities that underpin analytics, operational decision-making and emerging AI use cases, and may also help extend platform tooling where additional functionality is needed.
Qualifications
Required Qualifications
- 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 deformalized 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.
Preferred Qualifications
- 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 ability to identify when delivery problems would be better solved through reusable tooling or platform improvements
- An interest in developing long-term expertise within the firm
Skills & Technologies
About the Company
Goldman Sachs
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Sign in to applyJob Details
Employment Type
Full Time
Experience Level
Senior
Location
Dallas, TX
Posted
6 days ago
Country
US