refresh

Trending companies

Trending companies

Goldman Sachs
Goldman Sachs

The Goldman Sachs Group, Inc

Asset&Wealth Management-Senior Cloud Data Engineer-Vice President-Dallas at Goldman Sachs

RoleData Engineering
LevelVp
LocationDallas, Texas, United States
WorkHybrid
TypeFull-time
Posted1 day ago
Apply now

About the role

WM Data Engineering – Senior Cloud Data Engineer - Vice President Who We Look For:

Goldman Sachs Engineers are innovators and problem-solvers, building solutions for various divisions. We look for creative collaborators who evolve, adapt to change and thrive in a fast-paced global environment.

We are seeking a high-caliber, hands-on Senior Cloud Data Engineer. While you will provide architectural guidance, your primary impact will come from hands-on engineering: building production-ready data pipelines, containerizing microservices for Amazon ECS, and executing the technical migration of legacy on-premises systems to AWS.

Key Responsibilities:

  1. Hands-on Pipeline & Microservices Migration:
  • Active Migration Execution:

Directly execute the migration of legacy ETL and microservices to AWS. This includes refactoring monolithic code into containerized services and deploying them to Amazon ECS (Fargate/EC2).

  • Containerization & Orchestration:

Build and maintain Docker images, write complex ECS Task Definitions, and configure service-to-service communication using Amazon ECS Service Connect and AWS Cloud Map.

  • Data Pipeline Engineering:

Develop end-to-end data flows using AWS Glue (Py Spark), Amazon EMR, and Snowflake. Implement "Lakehouse" patterns using Apache Iceberg to ensure data portability.
2. Infrastructure & Automation-as-Code

  • IaC Development:

Write and maintain production-grade Terraform or AWS CDK modules to provision VPCs, ECS clusters, and RDS instances. Ensure all infrastructure is version-controlled and deployed via GitHub Actions or GitLab CI.

  • AI-Augmented Coding:

Actively use AI coding assistants (e.g., GitHub Copilot) to refactor legacy SQL, generate unit tests, and automate the creation of boilerplate pipeline code.

  • Toil Reduction:

Identify manual bottlenecks in the migration process and build custom automation tools in Python or Go to streamline data validation and schema conversion.
3. Technical Leadership & Reliability

  • Code Reviews & Standards:

Lead rigorous peer code reviews, enforcing standards for performance, security (IAM least privilege), and maintainability.

  • Observability Implementation:

Hands-on configuration of Amazon CloudWatch Container Insights, and Open Telemetry to ensure deep visibility into migrated microservices and data jobs.

  • Performance Tuning:

Directly optimize Spark job configurations, Snowflake warehouse sizing, and ECS auto-scaling policies to balance performance.

Qualifications:

Technical Requirements:

  • Experience:

8+ years of hands-on experience in Data Engineering and Cloud Infrastructure, with a focus on building and migrating production workloads.

  • AWS ECS Expertise:

Deep technical expertise in Amazon ECS (Fargate/EC2), including networking (ALB/NLB), task placement strategies, and container security.

  • Data Platform Expertise:

Proven experience with modern data platforms such as Snowflake(AI Data Cloud) and cloud-native services. Good understanding of open-source table formats, specifically Apache Iceberg, to enable interoperability, schema evolution, and high-performance analytics across multiple engines.

  • Programming:

Expert-level proficiency in Java,Python and SQL.

  • Big Data & Orchestration:

Hands-on experience with Spark, Kafka, and orchestration tools like Apache Airflow, Dagster, or dbt.

  • Data Modeling:

Deep understanding of data warehousing and modern data lakehouse architecture.

Leadership & Soft Skills:

  • Mentorship:

Proven track record of upskilling junior engineers.

  • Communication:

Ability to explain complex technical concepts to non-technical stakeholders in the wealth management business.

  • Problem Solving:

A "builder" mindset with the ability to navigate ambiguity in a fast-paced 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: https://www.goldmansachs.com/careers/footer/disability-statement.html

© 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.

Required skills

AWS

Data pipelines

Docker

ECS

PySpark

Terraform

Snowflake

Microservices

Total Views

0

Total Apply Clicks

0

Total Mock Apply

0

Total Bookmarks

0

About Goldman Sachs

Goldman Sachs

The Goldman Sachs Group, Inc. is an American multinational investment bank and financial services company. Founded in 1869, Goldman Sachs is headquartered in the Battery Park City neighborhood of Manhattan in New York City, with regional offices in many international financial centers.

45,000+

Employees

Lower Manhattan

Headquarters

$80B

Valuation

Reviews

2 reviews

2.9

2 reviews

Work-life balance

2.5

Compensation

3.0

Culture

2.0

Career

4.0

Management

2.5

45%

Recommend to a friend

Pros

Amazing career growth opportunities

Chill management at some locations

Work-life balance valued in certain roles

Cons

Toxic workplace culture

Codependent atmosphere

Confusing interview process

Salary Ranges

20,304 data points

Junior/L3

Mid/L4

Senior/L5

Junior/L3 · Analyst

6,923 reports

$112,993

total per year

Base

$97,759

Stock

-

Bonus

$15,234

$77,583

$166,892

Interview experience

4 interviews

Difficulty

3.5

/ 5

Duration

21-35 weeks

Experience

Positive 0%

Neutral 75%

Negative 25%

Interview process

1

Application Review

2

HR Screen/HireVue

3

Recruiter Screen

4

Superday/Panel Interview

5

Final Decision

Common questions

Behavioral/STAR

Technical Knowledge

Culture Fit

Past Experience

Case Study