Senior Data Platform Engineer for Reliability & AI

Charles Schwab Corporation; Westlake (TX); Presencial; USD 140.000 - 190.000; Jornada completa

Descripción de la vacante

Charles Schwab Corporation, in partnership with DAFgiving360, seeks a Manager Data Engineer to design, build, and operate a modern data platform in Westlake/Austin, TX. You will own data pipelines, reliability, and governance while enabling analytics and AI initiatives.

Collaborate with Analytics, Governance, and Technology to onboard sources, improve models, and deliver scalable, secure data products used across the organization.

Formación

• 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, software engineering, or related technical disciplines.
• Advanced SQL and data modeling expertise, with experience designing durable, business‑aligned data structures.
• Experience building and maintaining ETL/ELT pipelines, orchestration workflows, and data integration processes.
• Experience with cloud data platforms and modern warehouse/lake/lakehouse environments.
• Experience with medallion/lakehouse patterns and governed self‑service analytics.
• Experience supporting production systems, including monitoring, incident response, and operational reliability.
• Working knowledge of data governance, metadata, lineage, and data quality concepts.
• Proven ability to influence technical direction and partner cross‑functionally without direct authority.
• Strong problem‑solving, communication, and documentation skills.

Responsabilidades

• 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, alerting, and operational improvements.
• Support production operations, release activities, and business continuity planning as part of a shared team model.
• Partner with architects and engineers to implement modern data architecture and engineering standards.
• Onboard new data sources across raw, staging, and analytics‑ready layers.
• Simplify legacy data structures, reduce duplicated logic, and align models to business concepts.
• Implement data quality checks, automated testing, and observability practices.
• Partner with Data Governance on metadata, lineage, glossary, and stewardship standards.
• Ensure data solutions align with security, privacy, retention, and compliance requirements.
• Help identify and prevent recurring data defects across critical assets.
• Translate business and analytics needs into robust technical solutions.
• Recommend improvements that reduce manual effort and improve data accessibility.
• Contribute to technical standards, documentation, and engineering best practices.
• Communicate clearly with technical and non‑technical partners and influence direction through strong collaboration.
• Build foundational data assets that support advanced analytics, automation, machine learning, and future AI use cases.
• Improve consistency, usability, trust, and performance of data products that enable faster and more reliable decision‑making.
• Contribute to the long‑term evolution of DAFgiving360’s data infrastructure so it can scale with digital, analytics, operational, and AI‑enabled capabilities.

Conocimientos

SQL expertise

Data modeling

ETL/ELT pipelines

Cloud data platforms

Data governance concepts

Cross-functional influence

Communication

Documentation

Problem solving

Analytics engineering

Educación

Bachelor’s degree in CS/IS/Engineering/Analytics

Herramientas

BigQuery

SQL

Python

Google Cloud Platform

Oracle

ETL/ELT Orchestration

Git

CI/CD

PowerShell

Descripción del empleo

Charles Schwab Corporation, in partnership with DAFgiving360, seeks a Manager Data Engineer to design, build, and operate a modern data platform in Westlake/Austin, TX. You will own data pipelines, reliability, and governance while enabling analytics and AI initiatives.

Collaborate with Analytics, Governance, and Technology to onboard sources, improve models, and deliver scalable, secure data products used across the organization.