Software Engineering Data, Lakehouse and AI Data Platform Engineer Vice President

Goldman Sachs

Confirmed live 2 days ago High trust

Quick summary

Work type
On-site
Location
New York, NY
Salary
$130,000–$250,000 / yr
Posted
75 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $182k
This role $190k
$116k most similar roles pay here $264k

This role pays more than 62% of similar roles. Most pay $151,000–$214,000 — the shaded band above. At the midpoint, this role pays about $190k versus about $182k for comparable roles.

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.

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At a glance

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

Software Engineering - Data, Lakehouse and AI Data Platform Engineer - Vice President joins the Lakehouse and AI Data Platform team to build foundational data infrastructure for firm-wide AI and analytics 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 responsibilities include refactoring existing flows and ensuring production readiness through rigorous testing and reconciliation. Required skills include proficiency in Python or Java, SQL for analysis and optimization, and experience with Apache Spark, Kafka, and formats like JSON, Avro, and Parquet. The role addresses the challenge of creating reliable, high-performing data products within a modern Lakehouse environment using technologies such as Snowflake, Databricks, and Apache Iceberg.

What you'll do

  • Build, enhance, and support batch and streaming data pipelines on the Lakehouse and AI platform.
  • Refactor or 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.
  • Provide technical leadership, task breakdown, and guidance for junior engineers on complex workstreams.

What we're looking for

  • 7-12+ years of experience.
  • 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, including 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.
  • Ability to lead delivery for a workstream, manage dependencies, and support less experienced engineers.

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