Manager-Data Platform Engineer

Your opportunity

Schwab Description:

​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.

Schwab India:

​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

Role Description:

Schwab Asset Management (SAM) is a leading asset manager supporting mutual funds, ETFs, and managed account products governed under stringent regulatory and compliance requirements. SAM operates in a multi cloud, multi custodian, multi vendor ecosystem, relying on a diverse set of external platforms such as Vestmark, Aladdin, Eagle, and others to serve its investment, operational, and regulatory functions.
This role sits directly within SAM Data team, the team responsible for designing, building, operating, and enhancing SAM Data products , platform capabilities underpinning SAM Data platform. 

This role Manager – Schwab Asset management- Data Platform Engineer, owns end to end data capabilities—from ingestion and domain modeling to platform frameworks, Data APIs, and Python based visualization/UI layers—that power Schwab Asset Management’s investment, operational, analytical, and regulatory use cases.
This position is expected to operate as a senior technical contributor and platform leader, defining reusable frameworks, setting engineering standards, and driving consistency across the SAMDA ecosystem. The engineer partners closely with architects, product owners, and investment stakeholders to ensure scalable, governed, and business aligned data solutions.

Key Responsibilities:

​Platform Frameworks & Engineering Standards 
•Design and build reusable data platform frameworks for ingestion, transformation, validation, and consumption.
•Establish standardized patterns for data pipelines, APIs, and visualization layers across SAMDA.
•Define best practices for schema evolution, versioning, error handling, and observability.
•Influence platform roadmap through hands on engineering leadership.
Design & Build Advanced Data Pipelines
•Architect and implement complex, cloud native ETL/ELT pipelines supporting investment and analytical data.
•Build reliable workflows using GCS, Dataproc, Cloud Dataflow, Composer (Airflow), and Pub/Sub.
•Implement scalable transformations and curated layers in Snowflake and cloud data warehouses.
Investment Data Domain Focus
This role has deep ownership within the Investment Data domain, including but not limited to:
•Holdings, positions, transactions, cash flows, and security master data
•Portfolio, account, and instrument hierarchies
•Performance, risk, exposure, and attribution datasets
•Reference data, taxonomies, and domain models that support downstream analytics and reporting
The engineer is responsible for designing domain driven data models and operational data stores that accurately represent investment concepts and scale across multiple SAM products and platforms.
Investment Data Modeling & Domain Engineering
•Design enterprise grade investment data models using Kimball, relational, and domain driven design principles.
•Create operational and analytical data stores from the ground up, including taxonomies and canonical models.
•Ensure models support regulatory, performance, and investment analytics use cases.
Data APIs & Service Layer
•Design and implement Data APIs using Python (FastAPI / Flask) to expose curated investment datasets.
•Build scalable, secure RESTful services for analytical and operational consumers.
•Apply governance, access control, and data protection standards aligned with regulated environments.
Python Dashboards & Data Visualization
•Develop Python based dashboards and UI applications using Streamlit, Dash, Panel, or similar frameworks.
•Create interactive visualizations using Plotly, Matplotlib, and Seaborn to support investment insights.
•Translate complex investment data into intuitive, self service analytical experiences.
Advanced Cloud & Application Engineering
•Build data and application services using Cloud Run, Cloud Functions, and Cloud SQL.
•Apply distributed processing frameworks such as Apache Spark, Beam, and Flink.
•Package and deploy data services, APIs, and UI components using Docker.
DevOps, CI/CD & Automation
•Lead CI/CD design for pipelines, APIs, and visualization apps using Git, Bitbucket, Bamboo, Jenkins, and GitHub Actions.
•Implement automated testing, deployment, and release management patterns.
•Drive infrastructure automation using Terraform or Google Cloud Deployment Manager.
Data Quality, Reliability & Observability
•Define and implement data quality frameworks, reconciliation checks, and monitoring standards.
•Proactively identify and resolve complex data, platform, and application issues.
Technical Leadership & Collaboration
•Act as a senior technical leader and mentor for data engineers across SAMDA.
•Lead design reviews and influence cross team engineering decisions.
•Communicate complex platform and investment data concepts to technical and business stakeholders.

Required Qualifications:

Bachelor’s degree in Computer Science, Information Technology, or equivalent practical experience.
•6–8 years of experience building cloud based data platforms and enterprise data solutions.
•Strong experience in the Investment or Asset Management data domain.
•Hands on expertise with Snowflake and GCP services (GCS, Cloud Run, Cloud Functions, Pub/Sub, Composer, Cloud SQL).
•Advanced proficiency in Python for data engineering, API development, and visualization.
•Proven experience building REST APIs using Python frameworks (FastAPI, Flask, or equivalent).
•Experience with Python visualization and UI frameworks (Streamlit, Dash, Panel, or similar).
•Strong background with distributed processing frameworks (Spark, Beam, or Flink).
•Expertise in CI/CD, containerization (Docker), and infrastructure as code (Terraform or GCP Deployment Manager).

Tools & Technologies
•Cloud: GCP (GCS, Cloud Run, Cloud Functions, Pub/Sub, Cloud SQL, Composer)
•Data Warehouses: Snowflake, BigQuery
•Processing: Spark, Beam, Flink
•APIs: Python (FastAPI, Flask)
•Visualization/UI: Streamlit, Dash, Panel, Plotly, Matplotlib, Seaborn
•DevOps: Git, Bitbucket, Bamboo, Jenkins, GitHub Actions, Docker
•IaC: Terraform, Google Cloud Deployment Manager.

Preferred Qualifications:

Experience designing platform level frameworks adopted by multiple engineering teams.
•Deep understanding of regulated data environments, governance, lineage, and auditability.
•Strong grasp of modern data architecture and self service analytics patterns.
•Ability to influence platform strategy and mentor senior engineers.
•Excellent documentation and executive level communication skills