Vice President - Data Engineering

Asset & Wealth Management - PWM Data Engineering - Vice President - Hyderabad

Who We Are

At Goldman Sachs, we connect people, capital and ideas to help solve problems for our clients. We are a leading global financial services firm providing investment banking, securities and investment management services to a substantial and diversified client base that includes corporations, financial institutions, governments and individuals.

In Private Wealth Management, we help our clients pursue their wealth management goals through careful advice & astute investment management. PWM Engineering plays a pivotal role in building the tools and applications our business needs to effectively manage and support our client’s diverse requirements. We support the entire user experience starting with onboarding through to trading, reporting, as well as providing clients access to their portfolios online via native iOS and Android apps. We also build and support numerous applications for our Business and Operations users to help them effectively manage risk and provide the best white-glove service possible to our clients.

The Data Distribution team supports PWM's Quantum data distribution platform which is considered the primary source of data relating to Client Holdings, Transactions, Taxlots and reference data like Accounts, Products and Prices in PWM. Several teams/projects requires this data and our team has built several distribution channels  for different usage patterns.

We are currently enhancing our platform based on new business requirements as well as increasing stability and scalability needs to support a growing business. The platform will be required to manage very high volumes of requests with varying time sensitivities and prioritising across multiple tenants via an event based framework.

Your Impact

We are seeking a highly skilled and experienced Data Engineer / Cloud Specialist to join our dynamic data platform team. In this role, you will be responsible for designing, implementing, and managing scalable data infrastructure on Amazon Web Services (AWS). You will bridge the gap between traditional cloud architecture and modern data engineering, building robust pipelines that power our analytics, business intelligence, and AI/ML initiatives.

The ideal candidate is a hands-on technical expert who can architect complex data environments while remaining deeply involved in the development of ETL/ELT workflows. You will provide technical leadership, mentor junior engineers, and drive innovation by adopting emerging technologies such as Vector Databases, Data Mesh principles, and Real-time Streaming architectures.

Key Responsibilities

• Data Architecture & Infrastructure: Design and deploy enterprise-grade data environments on AWS, focusing on high availability, scalability, and cost-efficiency.
• Pipeline Development: Build and maintain complex ETL/ELT pipelines using AWS Glue, Apache Spark, and Python to ingest and transform data from diverse sources into data lakes and warehouses.
• Modern Data Stack Management: Manage and optimize cloud-native data platforms including Snowflake, Databricks, and Amazon Redshift, ensuring seamless integration with the broader AWS ecosystem.
• Streaming & Messaging: Implement real-time data processing solutions using Apache Kafka, Amazon Kinesis, or MSK to support event-driven architectures and sub-second analytics.
• Data Modeling: Collaborate with stakeholders to design optimized data models (Star Schema, Data Vault, or Medallion Architecture) that support both operational and analytical workloads.
• Automation & DevOps: Drive the adoption of Infrastructure as Code (IaC) using Terraform or AWS CloudFormation to automate the provisioning of data resources and CI/CD pipelines.
• Security & Governance: Implement robust data security practices, including encryption at rest/transit, Role-Based Access Control (RBAC), and data masking. 
• Performance Tuning: Monitor and optimize the performance of distributed compute clusters and database queries to ensure meeting Service Level Agreements (SLAs) while managing cloud spend (FinOps).
• Mentorship & Leadership: Act as a technical authority within the team, guiding junior members and contributing to the strategic evolution of the global data platform.

Basic Qualifications

• Education: Bachelor’s or higher in Computer Science, Data Science, or a related field.
• Experience:
  • 8+ years of experience in software development or data engineering in a commercial environment.
  • 5+ years of hands-on experience designing and managing data infrastructure on AWS.
  • 3+ years of experience in a senior or lead data engineering role.
• Technical Proficiency:
  • Deep understanding of AWS Data Services: S3, Glue, EMR, Lambda, Athena, RDS, DynamoDB, and Redshift.
  • Expertise in Python and SQL for data manipulation and automation.
  • Experience with orchestration tools such as Apache Airflow or Dagster.
  • Proficiency in Terraform for automating cloud infrastructure.
  • Experience with messaging systems like Kafka or SQS/SNS.
• Soft Skills: Strong communication skills with the ability to articulate technical trade-offs to both technical and non-technical stakeholders.

Preferred Qualifications

• Industry Experience: Experience in the financial services industry, particularly with high-volume transactional data.
• Certifications: AWS Certified Data Engineer – Associate/Professional or AWS Certified Solutions Architect – Professional.
• Advanced Tech: Familiarity with dbt (data build tool), Vector Databases (e.g., Pinecone, Weaviate), and Generative AI data preparation workflows.

Goldman Sachs Engineering Culture

At Goldman Sachs, our Engineers don’t just make things – we make things possible. Change the world by connecting people and capital with ideas. Solve the most challenging and pressing engineering problems for our clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity at the speed of markets.

Engineering is at the critical center of our business, and our dynamic environment requires innovative strategic thinking and immediate, real solutions. Want to push the limit of digital possibilities? Start here!

© The Goldman Sachs Group, Inc., 2026 All rights reserved.
Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity.

 

Experience Level

Executive Level