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 187 open roles on FindRole.

Listed pay typically runs $130,000–$250,000 across 60 roles with salary data.

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At a glance

TL;DR · Senior Cloud Data Engineer, Vice President

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As a Senior Cloud Data Engineer at Goldman Sachs, you will join a dynamic team focused on migrating legacy ETL and microservices to AWS. Your day-to-day responsibilities include hands-on engineering tasks such as containerizing applications for Amazon ECS, developing data pipelines with AWS Glue (PySpark) and Snowflake, and implementing "Lakehouse" patterns using Apache Iceberg. You will also develop infrastructure-as-code modules in Terraform or AWS CDK, automate manual processes with Python or Go scripts, and ensure observability through CloudWatch Container Insights and OpenTelemetry. The role requires expertise in AWS ECS, Snowflake, Java, Python, SQL, Spark, Kafka, and orchestration tools like Apache Airflow. Additionally, you will mentor junior engineers, communicate complex technical concepts to non-technical stakeholders, and optimize performance for migrated systems within the wealth management domain.

Skills

AWS Amazon ECS Terraform Python Java SQL Snowflake Apache Iceberg Docker CI/CD GitHub Actions GitLab CI OpenTelemetry Amazon CloudWatch Apache Airflow Kafka

What you'll do

Directly execute migration of legacy ETL and microservices to AWS.
Build and maintain Docker images for Amazon ECS deployment.
Develop end-to-end data flows using AWS Glue (PySpark) and Snowflake.
Write production-grade Terraform modules for provisioning cloud infrastructure.
Lead rigorous code reviews, enforcing performance and security standards.
Configure observability tools like CloudWatch Container Insights and OpenTelemetry.
Optimize Spark job configurations and ECS auto-scaling policies for performance.

What we're looking for

8+ years of hands-on experience in Data Engineering and Cloud Infrastructure.
Deep expertise in AWS ECS (Fargate/EC2) including networking and security.
Proven experience with Snowflake, Apache Iceberg, and modern data platforms.
Expert-level proficiency in Java, Python, and SQL.
Hands-on experience with Spark, Kafka, and orchestration tools like Airflow.
Deep understanding of data warehousing and lakehouse architecture.
Ability to mentor junior engineers and communicate complex concepts.