Data Platform Engineer: Pipelines & Quality

Goldman Sachs; Dallas (TX); On-site; USD 120,000 - 160,000; Full time

Job summary

Goldman Sachs is seeking a Software Engineer on the Data Platform team to design, build and operate data pipelines and curated datasets on the firm’s modern data stack. You will work across ingestion, transformation, modeling, optimization and data quality, delivering reliable, scalable data products for analytics, reporting and AI use cases while collaborating with platform and data consumers.

The role emphasizes production-grade data assets, working with modern data technologies, and growing

Qualifications

• Bachelor’s or master’s degree in a relevant discipline, or equivalent practical experience.
• 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.

Responsibilities

• Design, build, test and support data pipelines and curated datasets.
• Work across ingestion, transformation, modelling, optimization and data quality.
• Where there are gaps in platform functionality, contribute to shared tooling or framework components.
• Deliver data products that are reliable, scalable and fit for purpose.

Skills

Python

Java

SQL

CI/CD

Distributed processing

Data modeling

Data quality

Troubleshooting

Education

Bachelor’s or Master’s degree in a relevant discipline

Tools

Apache Spark

Kafka

Snowflake

Apache Iceberg

Databricks

Hadoop

Kubernetes

Job description

Goldman Sachs is seeking a Software Engineer on the Data Platform team to design, build and operate data pipelines and curated datasets on the firm’s modern data stack. You will work across ingestion, transformation, modeling, optimization and data quality, delivering reliable, scalable data products for analytics, reporting and AI use cases while collaborating with platform and data consumers.

The role emphasizes production-grade data assets, working with modern data technologies, and growing