Asset & Wealth Management-Cloud Engineer-Associate-Dallas
Goldman Sachs · Dallas, TX
- On site
- Full-time
- $100,000 / year
- Dallas, TX
Job highlights
- Build scalable AWS data platforms and ETL/ELT pipelines.
- Implement modern data patterns and Lakehouse architecture.
- Ensure data governance, security, and quality standards.
- Optimize cloud costs and performance with IaC.
- Support migration and AI/ML readiness initiatives.
About the role
Cloud Engineer Associate - WM Data Engineering
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.
Key skills/competency
- Cloud Engineering
- AWS
- Data Engineering
- ETL/ELT
- Apache Airflow
- Python
- SQL
- Spark
- Kafka
- Snowflake
Skills & topics
- Cloud Engineer
- AWS
- Data Engineering
- ETL
- ELT
- Python
- Java
- SQL
- Spark
- Kafka
- Snowflake
- Apache Airflow
- Associate
- Goldman Sachs
- Dallas
How to get hired
- Tailor your resume: Highlight AWS, data engineering, Python, Java, SQL, and ETL/ELT experience.
- Showcase cloud skills: Emphasize experience with Snowflake, Apache Iceberg, and Airflow.
- Prepare for technical questions: Be ready to discuss distributed systems and data architecture.
- Demonstrate problem-solving: Prepare examples of your 'builder' mindset and teamwork.
- Research Goldman Sachs: Understand their commitment to innovation and financial services.
Technical preparation
Master AWS services for data lakes and pipelines.,Practice Python, Java, and SQL for data manipulation.,Implement ETL/ELT pipelines using Airflow or Lambda.,Build using Terraform or AWS CDK for IaC.
Behavioral questions
Describe a complex technical problem you solved.,How do you ensure data quality and security?,Share an experience migrating systems to the cloud.,How do you collaborate with architects and teams?
Frequently asked questions
- What specific AWS services are crucial for this Cloud Engineer role at Goldman Sachs?
- This Cloud Engineer position heavily utilizes AWS services such as Amazon S3 (Data Lake), AWS Glue, Amazon Redshift, Amazon Athena, AWS Step Functions, Managed Workflows for Apache Airflow (MWAA), AWS Lambda, AWS KMS, and AWS Lake Formation. Familiarity with these services is key.
- How does Goldman Sachs approach data governance and security for their Cloud Engineer?
- Goldman Sachs enforces strict data governance and security. As a Cloud Engineer, you'll apply internal security standards, adhere to financial regulations like GDPR and CCPA, and implement IAM policies, data encryption using AWS KMS, and access controls via AWS Lake Formation.
- What programming languages are essential for the Cloud Engineer Associate role?
- Proficiency in Java, Python, and SQL is essential for this Cloud Engineer Associate role. These languages are critical for developing and maintaining data pipelines and interacting with modern data platforms.
- What is the expected experience level for the Associate Cloud Engineer at Goldman Sachs?
- The role requires approximately 5 years of experience in Data Engineering or Cloud Development, with a strong focus on distributed systems. This aligns with the Associate level at Goldman Sachs.
- Does Goldman Sachs use Infrastructure as Code (IaC) for their cloud deployments?
- Yes, Goldman Sachs utilizes Infrastructure as Code (IaC) for cloud deployments. As a Cloud Engineer, you'll be expected to use tools like Terraform, AWS CDK, or CloudFormation for consistent infrastructure management.
- What are the key modern data patterns mentioned for this Cloud Engineer position?
- This Cloud Engineer role focuses on implementing modern data patterns, specifically the Lakehouse architectural pattern. This approach supports high-performance analytics across various business units by combining data lake and data warehouse capabilities.
- How can I best prepare my resume for the Goldman Sachs Cloud Engineer Associate job?
- To prepare your resume for the Cloud Engineer Associate role at Goldman Sachs, emphasize your experience with AWS cloud services, data engineering principles, Python, Java, SQL, and orchestration tools like Apache Airflow. Highlight any experience with Snowflake and Apache Iceberg.