
The Goldman Sachs Group, Inc
Asset & Wealth Management - PWM Data Engineering - Analyst - Bengaluru at Goldman Sachs
About the role
Who We Are
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. Goldman Sachs Engineers are innovators and problem-solvers, building solutions in risk management, big data, mobile and more. We look for creative collaborators who evolve, adapt to change, and thrive in a fast-paced global environment. Want to push the limit of digital possibilities? Start here.
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 prioritizing across multiple tenants via an event based framework.
Your Impact
We are looking for a motivated Junior Cloud SRE Analyst with 1–2 years of experience to join our Data Engineering team. In this role, you will help bridge the gap between software development and systems operations by applying engineering mindsets to operational challenges. You will focus on improving the reliability, scalability, and performance of our cloud-native applications while learning to manage complex distributed systems at scale.
As a junior member of the team, you will work under the guidance of senior leads to monitor system health, automate repetitive tasks (toil), and support incident response efforts. This is an ideal role for an early-career professional looking to deepen their expertise in AWS/Azure/GCP,Kubernetes, and Infrastructure as Code (IaC).
Key Responsibilities:
- Observability & Monitoring: Assist in maintaining and enhancing our monitoring stack (e.g., Prometheus, Grafana, Datadog). You will help build dashboards and configure alerts to ensure high visibility into system performance and Service Level Indicators (SLIs).
- Incident Support: Participate in the incident management lifecycle. You will assist senior engineers in troubleshooting production issues, performing initial triage, and documenting findings in post-mortem reports to prevent recurrence.
- Toil Reduction & Automation: Identify repetitive manual tasks and develop small-scale automation scripts (using Python, Go, or Bash) to improve operational efficiency and reduce "toil."
- Infrastructure as Code (IaC): Support the deployment and management of cloud infrastructure using tools like Terraform or Ansible. You will assist in making configuration changes and ensuring environment consistency.
- CI/CD Pipeline Support: Work with development teams to support and troubleshoot automated deployment pipelines (GitHub Actions, GitLab CI, or Jenkins), ensuring safe and reliable code releases.
- Documentation: Create and maintain technical documentation, including "runbooks" and "playbooks," to standardize response procedures for common system alerts.
- Capacity Awareness: Assist in tracking resource utilization and cloud spend, helping the team perform basic capacity planning to support application growth.
Basic Qualifications
- Bachelor’s or higher in Computer Science (or equivalent work experience)
- Experience: 1–2 years of experience in a technical role such as Cloud Support, Systems Administration, or Junior DevOps/Software Engineering.
- Cloud Foundations: Basic hands-on experience with at least one major cloud provider (AWS, Azure, or GCP), including familiarity with IAM, VPCs, and compute services.
- Scripting Proficiency: Ability to write and debug basic scripts in Python, Bash, or PowerShell for task automation.
- Linux Fundamentals: Comfortable working in a Linux/Unix environment, including command-line navigation, log analysis, and basic networking troubleshooting.
- Containerization: Foundational understanding of Docker and basic concepts of container orchestration (Kubernetes).
- Soft Skills: Strong analytical problem-solving skills, a high degree of curiosity, and the ability to remain calm and methodical during technical disruptions.
Preferred Qualifications
- Familiarity with SRE concepts such as **SLOs (Service Level Objectives)**and Error Budgets.
- Experience with version control systems, specifically Git.
- Basic knowledge of SQL and database management.
- Relevant certifications (e.g., AWS Certified Cloud Practitioner, CKA, or Azure Fundamentals).
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., 2021. All rights reserved.
Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity
Required skills
Data engineering
Scalable systems
Data platforms
Software engineering
Problem solving
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About Goldman Sachs

Goldman Sachs
PublicThe 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
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