Associate Software Engineering Data, Lakehouse and AI Data Platform Engineer

Goldman Sachs

Confirmed live 2 days ago High trust

Quick summary

Work type: On-site
Location: Dallas, TX
Posted: 51 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

How this pay compares to similar roles

Similar $184k

$136k most similar roles pay here $235k

This listing doesn't post a salary. Most similar roles pay $145,425–$222,437.

Based on 240 similar postings.

Employer

About Goldman Sachs

Goldman Sachs is a leading global investment banking, securities, and investment management firm providing financial services to corporations, financial institutions, governments, and individuals.

Goldman Sachs currently has 134 open roles on FindRole.

Listed pay typically runs $137,000–$250,000 across 55 roles with salary data.

Most-posted roles

View all roles at Goldman Sachs

At a glance

TL;DR · Associate Software Engineering Data, Lakehouse and AI Data Platform Engineer

Role Posting Log in to save

Software Engineering - Data, Lakehouse and AI Data Platform Engineer - Associate works within the Lakehouse and AI Data Platform team to build foundational data infrastructure for firm-wide analytics and AI capabilities. The role involves designing, building, and supporting batch and streaming data pipelines, creating curated datasets, and implementing robust data quality controls. You will manage ingestion, transformation, modeling, and optimization while developing shared tooling to improve platform functionality. Key technical requirements include proficiency in Python or Java, SQL for troubleshooting and optimization, and experience with distributed processing frameworks like Apache Spark. You will work with data formats such as JSON, Avro, and Parquet within a stack including Snowflake, Databricks, and Kafka. The role solves the challenge of providing reliable, well-governed, and high-performing data products to support operational decision-making and emerging AI use cases.

Skills

Python Java SQL Apache Spark Kafka Snowflake Databricks Apache Iceberg Hadoop Kubernetes CI/CD JSON Avro Parquet Sybase IQ Distributed Data Processing

What you'll do

Build, enhance, and support batch and streaming data pipelines on the Lakehouse and AI platform.
Refactor and modernize existing data flows to improve reliability, performance, and maintainability.
Develop raw, refined, and curated datasets for analytics, reporting, and AI use cases.
Apply data modeling principles to represent business entities and historical changes accurately.
Implement controls to validate the completeness, accuracy, and consistency of data across pipelines.
Build reusable tooling and framework components to improve platform functionality and operational support.
Perform root-cause analysis and troubleshooting for data quality issues in production environments.
Lead technical design and mentor junior engineers on implementation standards and code quality.

What we're looking for

Bachelor’s or master’s degree in a relevant discipline, or equivalent practical experience with strong quantitative skills.
Strong hands-on programming experience in Python or Java.
Good working knowledge of SQL, including troubleshooting, optimization, and data analysis.
Familiarity with software engineering fundamentals such as version control, testing, release discipline, and CI/CD practices.
Experience building production data pipelines using distributed processing frameworks like Apache Spark.
Working knowledge of common data formats such as JSON, Avro, and Parquet.
Understanding of temporal data modeling, schema design, and techniques to improve performance at scale.
Ability to lead delivery for a workstream and support less experienced engineers (preferred).