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Senior Cloud Data Engineer – lead architectural and hands‑on migration to AWS at Goldman Sachs.
Drive production pipelines, containerize microservices, and optimize data flows with Snowflake and Apache Iceberg.
WM Data Engineering – Senior Cloud Data Engineer – Vice President
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.
Key Responsibilities:
Hands-on Pipeline & Microservices Migration:
Active Migration Execution: Directly execute the migration of legacy ETL and microservices to AWS. This includes refactoring monolithic code into containerized services and deploying them to Amazon ECS (Fargate/EC2).
Containerization & Orchestration:
Build and maintain Docker images, write complex ECS Task Definitions, and configure service‑to‑service communication using Amazon ECS Service Connect and AWS Cloud Map.
Data Pipeline Engineering:
Develop end‑to‑end data flows using AWS Glue (PySpark), Amazon EMR, and Snowflake. Implement "Lakehouse" patterns using Apache Iceberg to ensure data portability.
Infrastructure & Automation-as-Code
IaC Development:
Write and maintain production‑grade Terraform or AWS CDK modules to provision VPCs, ECS clusters, and RDS instances. Ensure all infrastructure is version‑controlled and deployed via GitHub Actions or GitLab CI.
AI-Augmented Coding:
Actively use AI coding assistants (e.g., GitHub Copilot) to refactor legacy SQL, generate unit tests, and automate the creation of boilerplate pipeline code.
Toil Reduction:
Identify manual bottlenecks in the migration process and build custom automation tools in Python or Go to streamline data validation and schema conversion.
Technical Leadership & Reliability
Code Reviews & Standards:
Lead rigorous peer code reviews, enforcing standards for performance, security (IAM least privilege), and maintainability.
Observability Implementation:
Hands‑on configuration of Amazon CloudWatch Container Insights, and OpenTelemetry to ensure deep visibility into migrated microservices and data jobs.
Performance Tuning:
Directly optimize Spark job configurations, Snowflake warehouse sizing, and ECS auto‑scaling policies to balance performance.
Qualifications:
Technical Requirements Experience: 8+ years of hands‑on experience in Data Engineering and Cloud Infrastructure, with a focus on building and migrating production workloads. AWS ECS Expertise: Deep technical expertise in Amazon ECS (Fargate/EC2), including networking (ALB/NLB), task placement strategies, and container security. Data Platform Expertise: 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.
Technical Requirements
Experience: 8+ years of hands‑on experience in Data Engineering and Cloud Infrastructure, with a focus on building and migrating production workloads. AWS ECS Expertise: Deep technical expertise in Amazon ECS (Fargate/EC2), including networking (ALB/NLB), task placement strategies, and container security. Data Platform Expertise: 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.
Experience:
8+ years of hands‑on experience in Data Engineering and Cloud Infrastructure, with a focus on building and migrating production workloads.
AWS ECS Expertise:
Deep technical expertise in Amazon ECS (Fargate/EC2), including networking (ALB/NLB), task placement strategies, and container security.
Data Platform Expertise:
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 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.