Asset & Wealth Management-Cloud Engineer-Associate-Dallas

WM Data Engineering - Cloud Engineer - Software Engineer - Associate

Who 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:

1. 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.
   
   
2. 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.
   
   
3. 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.
   
   
4. 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.