Data Engineer

Charles Schwab Inc.•Austin, TX

7d•$48 - $61•Onsite

About The Position

At Schwab, you’re empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us challenge the status quo and transform the finance industry together. We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location(s). Schwab Technology Services is shaping the future of how clients manage their money by delivering innovative, reliable technology solutions. As a Data Engineer, you will design, develop, and maintain enterprise data assets, pipelines, reporting capabilities, and business intelligence solutions that support informed decision-making, regulatory reporting, and continuous improvement. You will collaborate with business partners, architects, engineers, and distributed delivery teams to translate complex requirements into scalable, high-quality solutions. Your work will include data integration, modeling, analysis, performance tuning, and production support while ensuring solutions align with architecture standards and development practices. You will also provide technical guidance to junior engineers and vendor partners, identify opportunities to simplify or reuse systems, and apply analytical thinking and sound judgment to deliver reliable outcomes.

Requirements

Bachelor’s degree in Computer Science/Information Technology or a related field, or equivalent practical experience.
5+ years of professional experience in development, support, and maintenance of ETL and database applications
2+ years of hands-on experience with GCP technologies (GCS, BigQuery, Dataproc)
2+ years of hands-on experience with IDMC (Informatica Intelligent Data Management Cloud)
2+ years of experience with Control M
Strong SQL knowledge, shell scripting and deep understanding of relational database concepts
Familiar and comfortable with agile development techniques
Familiarity with SCM and DevOps tool suites and CI/CD best practices; examples include Git (GitHub, GitLab, Bitbucket, etc.), Bamboo etc
Critical-thinking and strong problem-solving skills with ability to analyze and understand data.

Nice To Haves

Experience within the financial services industry
Ability to use Data Analysis and Metrics Analysis to identify trends and support actionable decisions
Strong Communication and Cross-Functional Collaboration skills across business, technical, onshore, and offshore teams

Responsibilities

Design, develop, and maintain enterprise data assets, pipelines, reporting capabilities, and business intelligence solutions.
Support informed decision-making, regulatory reporting, and continuous improvement.
Collaborate with business partners, architects, engineers, and distributed delivery teams to translate complex requirements into scalable, high-quality solutions.
Perform data integration, modeling, analysis, performance tuning, and production support.
Ensure solutions align with architecture standards and development practices.
Provide technical guidance to junior engineers and vendor partners.
Identify opportunities to simplify or reuse systems.
Apply analytical thinking and sound judgment to deliver reliable outcomes.