Hyderabad, Telangana, India
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Early. Similar jobs usually come down between day 6 and day 54.
At Charles Schwab, jobs usually come down by about day 34.
From 11,206 similar postings that came down, and 98 of Charles Schwab’s. Coming down is not always a hire.
18 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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Key Responsibilities: Design & Build Investment Data Pipelines • Design, develop, and optimize investment data pipelines using ETL/ELT patterns. • Integrate data from custodians, vendors, and internal platforms into curated datasets. • Build reliable workflows using GCS, Dataproc, Cloud Dataflow, Composer (Airflow), and Pub/Sub. • Implement scalable transformations in Snowflake and other cloud data warehouses. Investment Data Modeling • Contribute to portfolio, transaction, pricing, and performance data models aligned to investment use cases. • Apply Kimball/star schema patterns and domain driven modeling for analytics and reporting. • Optimize schemas for API consumption, dashboards, and quantitative analysis. Data APIs for Investment Use Cases (Full Stack) • Design and implement Investment Data APIs using Python • Expose curated investment datasets (holdings, performance, risk metrics) via secure REST endpoints. • Enable programmatic access for portfolio managers, analysts, and downstream applications. • Apply authentication, authorization, and data entitlement controls consistent with regulated investment data. Python Dashboards & Investment Analytics UI • Build Python based dashboards and UI applications (Streamlit, Dash, Panel). • Create interactive visualizations for portfolio views, performance trends, and risk insights using Plotly, Matplotlib, and Seaborn. • Translate complex investment datasets into intuitive, self service analytical experiences. • Optimize dashboard performance for large portfolios and time series data. Advanced Cloud & Application Engineering • Build data and application services using Cloud Run, Cloud Functions, and Cloud SQL. • Apply distributed processing frameworks (Apache Spark, Beam, Flink) for large scale investment datasets. • Package and deploy APIs and dashboards using Docker. DevOps, CI/CD & Automation • Own CI/CD pipelines for data pipelines, investment data APIs, and Python UI applications. • Use Git/Bitbucket/Bamboo, Jenkins, GitHub Actions, Maven, Nexus for build and release automation. Data Quality, Controls & Reliability (Investments) • Implement data quality checks specific to investment data (reconciliation, completeness, timeliness). • Monitor pipelines, APIs, and dashboards to ensure reliable delivery of investment insights. • Troubleshoot complex data issues impacting portfolio, performance, or risk reporting. Required Qualifications:
Required Qualifications: • Bachelor’s degree in Computer Science, Information Technology, or equivalent experience. • 3–5 years of experience building cloud based investment or financial data platforms. • Hands on experience with Snowflake and GCP services (GCS, Cloud Run, Cloud Functions, Pub/Sub, Composer, Cloud SQL). • Strong Python skills for data engineering, API development, and visualization. • Experience building REST APIs using FastAPI, Flask, or similar frameworks. • Experience building Python dashboards/UI (Streamlit, Dash, Panel). • Experience with distributed processing frameworks (Spark, Beam, or Flink). • Proficiency with CI/CD, Docker, and IaC (Terraform or GCP Deployment Manager). Preferred Qualifications:
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New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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.
Key Responsibilities:
Design & Build Investment Data Pipelines
• Design, develop, and optimize investment data pipelines using ETL/ELT patterns.
• Integrate data from custodians, vendors, and internal platforms into curated datasets.
• Build reliable workflows using GCS, Dataproc, Cloud Dataflow, Composer (Airflow), and Pub/Sub.
• Implement scalable transformations in Snowflake and other cloud data warehouses.
Investment Data Modeling
• Contribute to portfolio, transaction, pricing, and performance data models aligned to investment use cases.
• Apply Kimball/star schema patterns and domain driven modeling for analytics and reporting.
• Optimize schemas for API consumption, dashboards, and quantitative analysis.
Data APIs for Investment Use Cases (Full Stack)
• Design and implement Investment Data APIs using Python
• Expose curated investment datasets (holdings, performance, risk metrics) via secure REST endpoints.
• Enable programmatic access for portfolio managers, analysts, and downstream applications.
• Apply authentication, authorization, and data entitlement controls consistent with regulated investment data.
Python Dashboards & Investment Analytics UI
• Build Python based dashboards and UI applications (Streamlit, Dash, Panel).
• Create interactive visualizations for portfolio views, performance trends, and risk insights using Plotly, Matplotlib, and Seaborn.
• Translate complex investment datasets into intuitive, self service analytical experiences.
• Optimize dashboard performance for large portfolios and time series data.
Advanced Cloud & Application Engineering
• Build data and application services using Cloud Run, Cloud Functions, and Cloud SQL.
• Apply distributed processing frameworks (Apache Spark, Beam, Flink) for large scale investment datasets.
• Package and deploy APIs and dashboards using Docker.
DevOps, CI/CD & Automation
• Own CI/CD pipelines for data pipelines, investment data APIs, and Python UI applications.
• Use Git/Bitbucket/Bamboo, Jenkins, GitHub Actions, Maven, Nexus for build and release automation.
Data Quality, Controls & Reliability (Investments)
• Implement data quality checks specific to investment data (reconciliation, completeness, timeliness).
• Monitor pipelines, APIs, and dashboards to ensure reliable delivery of investment insights.
• Troubleshoot complex data issues impacting portfolio, performance, or risk reporting.
Required Qualifications:
• Bachelor’s degree in Computer Science, Information Technology, or equivalent experience.
• 3–5 years of experience building cloud based investment or financial data platforms.
• Hands on experience with Snowflake and GCP services (GCS, Cloud Run, Cloud Functions, Pub/Sub, Composer, Cloud SQL).
• Strong Python skills for data engineering, API development, and visualization.
• Experience building REST APIs using FastAPI, Flask, or similar frameworks.
• Experience building Python dashboards/UI (Streamlit, Dash, Panel).
• Experience with distributed processing frameworks (Spark, Beam, or Flink).
• Proficiency with CI/CD, Docker, and IaC (Terraform or GCP Deployment Manager).
Preferred Qualifications:
• Experience with investment management data (portfolios, performance, risk, pricing).
• Familiarity with custodians, portfolio accounting, or market data vendors.
• Knowledge of data governance, entitlements, and controls in regulated investment environments.
• Ability to lead cross functional investment data initiatives.
• Strong documentation and communication skills.
At Schwab India, you’re empowered to shape your future. We support your growth through meaningful work, continuous learning, and a culture rooted in trust and collaboration – so you can build the skills to make a lasting impact. Our benefits are designed to care for your wellbeing, your family, and your long-term financial security.
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Hyderabad, Telangana, India
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