Sr Specialist - Data Engineering

Your opportunity

At Charles Schwab, our purpose is simple: we champion client’s goals with passion and integrity. Guided by honesty, mutual respect and a commitment to doing what’s right, we bring innovation, education, and service together to help shape financial futures. Our people are the foundation of our success – they approach their work with curiosity and collaboration, coming together to create solutions that make a meaningful impact for clients and communities. As we expand into India, we are bringing this same culture of inclusion, learning, and opportunity to new talent. Joining us means becoming part of a global team where your work matters and your future can take shape.

Our Hyderabad location is central to Schwab’s growth, bringing together talented people and technology to drive innovation, scale and efficiency. Here, you will work alongside teams who create solutions that support millions of clients every day. The work you do is more than daily operations – it’s a chance to experiment, learn, and build within a values-driven, supportive environment. This is a unique opportunity to be part of our early growth phase and shape something new, backed by the stability and strength of a Fortune 500 company. Your impact begins on day one, and your contributions will help define our future in the region​.

What you have

Key Responsibilities:

Apply knowledge and take a lead role in implementing quantitative investment research products within the designated business area to support organizational goals and objectives, including gathering and collecting time series financial data, and developing quantitative models, analytics, and tests  

Develop control frameworks required to deploy and manage quant models in production environments. 

Lead data engineering implementation efforts for data processing pipelines that curate financial datasets into representations fit for model research and production applications. 

Co-develop production code in conjunction with quant researchers to deliver performant software (supported by comprehensive test coverage) that meet investment objectives while minimizing the risk of model errors; manage SDLC processes to enable CI/CD. 

Build data visualizations and other tooling to enable model researchers to efficiently monitor model performance and stability, as well as to interpret model outputs. 

Required Qualifications:

Degree in computer science, information systems, math, engineering, or other technical field, or equivalent experience 

Three plus years of experience with Python or Java 

Proficiency in one or more programming languages used for quantitative investment model development and analysis (e.g Python or R) 

Experience building data pipelines and related processes with large financial research timeseries datasets 

Proficiency in designing quant-research optimized data models that support efficient data retrieval and aggregation of financial datasets, including complex hierarchical structures 

Familiarity in developing distributed data processing and streaming frameworks and architectures 

Experience leveraging continuous integration/development tools (e.g. Jenkins, Docker, Containers, OpenShift, Kubernetes, and container automation) in a CI/CD pipeline 

Refines data analysis approaches to support informed business decision-making 
Enhances processes to ensure legal and ethical data compliance 

Innovates solutions to enhance data visualization clarity and utility 

Develops continuous monitoring mechanisms to ensure compliance and optimize performance of quantitative models in production 

Utilizes statistical techniques and hypothesis testing to analyze large datasets to support decision-making 

Leverages expertise in quantitative systems architecture to enhance the business impact of software solutions 

Optimizes software development testing and verification to enhance component reliability and address operational problems