The Senior Cloud Data Engineer at Goldman Sachs will play a crucial role in migrating legacy systems to AWS while providing architectural guidance. This hands-on position focuses on building production-ready data pipelines and containerizing microservices for Amazon ECS. The ideal candidate will thrive in a fast-paced environment and collaborate with various divisions to innovate and solve complex problems. The role requires a blend of technical expertise and leadership skills to mentor junior engineers and ensure high standards in code quality and performance.

• 8+ years of hands-on experience in Data Engineering and Cloud Infrastructure.
• Deep technical expertise in Amazon ECS (Fargate/EC2) and networking.
• Proven experience with modern data platforms such as Snowflake.
• Expert-level proficiency in Java, Python, and SQL.
• Hands-on experience with Spark, Kafka, and orchestration tools.

• Directly execute the migration of legacy ETL and microservices to AWS.
• Build and maintain Docker images and write complex ECS Task Definitions.
• Develop end-to-end data flows using AWS Glue, Amazon EMR, and Snowflake.
• Write and maintain production-grade Terraform or AWS CDK modules.
• Lead rigorous peer code reviews and enforce performance and security standards.

• Employees at Goldman Sachs are often offered comprehensive benefits, including medical, dental, life and disability coverage, generous vacation and holidays, and robust wellness resources such as EAP counseling, medical advocacy, on-site/virtual health services, and fitness support. Financial perks typically include retirement savings programs, live financial education, education support, and wealth-creation opportunities through equity awards and select investment programs. Many locations also provide family benefits (childcare resources, parental and family leaves, adoption/surrogacy support) and flexible work options like part-time schedules, job sharing, telecommuting, and alternate hours.