Job DescriptionWM Data Engineering - Cloud Engineer - Software Engineer - AssociateWho We Look For: Goldman Sachs Engineers are innovators and problem-solvers who thrive in fast-paced global environments. We are seeking a motivated Cloud Engineer to support the WM Data Engineering ecosystem. This role focuses on executing technical blueprints and transitioning legacy on-premises constraints into scalable, cloud-native solutions. You will work closely with senior architects to ensure data assets are migrated seamlessly, securely, and cost-effectively.
Key Responsibilities: - Architecture & Design Implementation:
- Cloud-Native Development: Assist in building scalable data platforms using AWS services such as Amazon S3 (Data Lake), AWS Glue, Amazon Redshift, and Amazon Athena.
- Pipeline Development: Develop and maintain automated ETL/ELT pipelines for batch and real-time processing using AWS Step Functions, Managed Workflows for Apache Airflow (MWAA), or AWS Lambda.
- Modern Data Patterns: Implement Lakehouse architectural patterns to support high-performance analytics across business units.
- Data Governance & Security:
- Compliance & Security: Apply internal security standards and adhere to financial regulations (e.g., GDPR, CCPA, SOC2). Implement IAM policies, data encryption (AWS KMS), and access controls via AWS Lake Formation.
- Data Quality: Execute frameworks for automated data quality checks and maintain metadata management to ensure trusted reporting.
- Cloud Optimization:
- Cost & Performance: Support cost-management initiatives using S3 Intelligent-Tiering and serverless scaling. Monitor pipeline throughput to meet Service Level Agreements (SLAs).
- Infrastructure as Code (IaC): Utilize Terraform, AWS CDK, or CloudFormation for consistent infrastructure deployments.
- Modernization:
- Migration Support: Contribute to the migration of on-premises data workloads to AWS.
- AI/ML Readiness: Help build the data foundations required for predictive modeling and generative AI applications.
Qualifications: Technical Requirements
- Experience: Approximately 5 years of experience in Data Engineering or Cloud Development, with a focus on distributed systems.
- Technical Skills:
- Experience with modern data platforms like Snowflake and cloud-native AWS services.
- Understanding of open-source table formats, specifically Apache Iceberg.
- Proficiency in Java, Python, and SQL.
- Hands-on experience with Spark, Kafka, and orchestration tools like Apache Airflow, Dagster, or dbt.
- Soft Skills: Strong problem-solving "builder" mindset and the ability to communicate technical concepts within a team 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: ;br>
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.
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