Who We Look For:

Goldman Sachs Engineers are innovators and problem-solvers, building solutions for various divisions. We look for creative collaborators who evolve, adapt to change and thrive in a fast-paced global environment.

We are seeking a high-caliber, hands-on Data Engineering Manager to lead our Wealth Data Engineering team in Birmingham. In this pivotal role, you will be responsible for the architectural vision and operational excellence of our data platforms. You will not only manage a team of talented engineers but also "raise the bar" by contributing to code, designing scalable cloud architectures, and ensuring our data ecosystem is fully optimized for Advanced Analytics and Artificial Intelligence (AI).

As the local lead, you will bridge the gap between complex financial data requirements and cutting-edge engineering solutions, ensuring our wealth management services are powered by reliable, real-time, and AI-ready data.

Key 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 Data Ops.
• 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 the local tech community and internal engineering forums.

Qualifications:

Technical Requirements:

• 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.

ABOUT GOLDMAN SACHS:

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.

We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers.

We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html

© The Goldman Sachs Group, Inc., 2023. All rights reserved.

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.