Lead Data Platform Engineer

Charles Schwab Corporation; Westlake (TX); On-site; USD 130,000 - 170,000; Full time

Job summary

Charles Schwab & Co., Inc. is seeking a Senior Data Engineer to design, build, operate, and evolve a modern data platform for DAFgiving360.

You will lead hands-on engineering across ingestion, transformation, quality, and governance to support analytics and AI initiatives. Collaborate with Analytics, Governance, Technology, and Product peers to reduce data complexity, improve accessibility, and ensure reliable, scalable data foundations for future AI-enabled capabilities.

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Analytics, or related field, or equivalent experience.
• 7+ years of experience in data engineering, data architecture, analytics engineering, or related technical disciplines.
• Advanced SQL and data modeling expertise, with experience designing durable, business‑aligned data structures.

Responsibilities

• Build and maintain scalable ingestion, transformation, and integration pipelines.
• Develop reusable data products and shared engineering patterns.
• Improve platform reliability, performance, and maintainability through monitoring and operational improvements.
• Support production operations, release activities, and business continuity planning.

Skills

Advanced SQL

Data modeling

ETL/ELT pipelines

Python

Google Cloud Platform

BigQuery

Data warehousing

Data governance

Cloud data platforms

CI/CD

Education

Bachelor’s degree in Computer Science, Information Systems, Engineering, Analytics, or related field

Tools

Oracle

GCS

Job description

Charles Schwab & Co., Inc. is seeking a Senior Data Engineer to design, build, operate, and evolve a modern data platform for DAFgiving360.

You will lead hands-on engineering across ingestion, transformation, quality, and governance to support analytics and AI initiatives. Collaborate with Analytics, Governance, Technology, and Product peers to reduce data complexity, improve accessibility, and ensure reliable, scalable data foundations for future AI-enabled capabilities.