Responsibilities

Team Leadership: Lead and mentor a local team of data engineers in Birmingham. Foster a culture of technical excellence, continuous learning, and agile delivery. Platform Ownership: Own the end‑to‑end data lifecycle. Design, build, and maintain robust data platforms and pipelines that handle large‑scale, multi‑structured wealth data. AI Readiness: Implement strategies to make data "AI-ready," focusing on data quality, low‑latency access, and the integration of MLOps principles into the data engineering workflow. Technical Governance: Set and enforce high standards for code quality, documentation, and testing. Drive the adoption of modern engineering practices like CI/CD, Infrastructure as Code (Terraform), and DataOps. Stakeholder Management: Collaborate with Data Scientists, Product Managers, and Application teams to translate business needs into scalable technical solutions. Local Advocacy: Act as the technical face of the team in the Birmingham office, contributing to local tech community engagement and internal engineering forums.

Qualifications

Experience: 10+ years in Data Engineering, with at least 2+ years in a formal leadership or management role. Data Platform Mastery: Proven experience with modern data platforms such as Snowflake (AI Data Cloud) and cloud‑native services. Good understanding of open‑source table formats, specifically Apache Iceberg, to enable interoperability, schema evolution, and high‑performance analytics across multiple engines. Programming: Expert‑level proficiency in Java, Python and SQL. Big Data & Orchestration: Hands‑on experience with Spark, Kafka, and orchestration tools like Apache Airflow, Dagster, or dbt. Data Modeling: Deep understanding of data warehousing and modern data lakehouse architecture. Leadership & Soft Skills: Mentorship: Proven track record of upskilling junior and senior engineers. Communication: Ability to explain complex technical concepts to non‑technical stakeholders in the wealth management business. Problem Solving: A "builder" mindset with the ability to navigate ambiguity in a fast‑paced environment. Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.

Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law. #J-18808-Ljbffr