Data Engineer
Confirmed on the employer's own hiring board on Nov 5, 2026. First seen by Alion on Nov 5, 2026. Charles Schwab scores A on the Alion truth index.
Your Opportunity
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 is seeking a results-oriented Senior Data Engineering to join the Operational Data Exchange (ODX) Technology team within Schwab Data. This team plays a critical role in delivering operational intelligence and enterprise data solutions that support key business functions across Schwab primarily supporting Schwab Technology Services (STS).
In this role, you will help advance Schwab’s transformation into a data-driven organization by developing scalable, high-performing data solutions on a modern cloud-based data platform. You will partner closely with engineers, technical leads, analysts, and business stakeholders to design, build, and optimize data pipelines that deliver trusted, actionable insights across the enterprise. Your work will directly contribute to improving system stability, accelerating time to market, enabling operational efficiency, and supporting informed business decision-making.
As a hands-on data engineering professional, you will leverage cloud technologies, data integration tools, and software engineering best practices to create reliable end-to-end data solutions. You will contribute throughout the development lifecycle, from analyzing business requirements and translating them into technical designs to implementing data quality controls, supporting production deployments, and driving continuous improvement initiatives. Success in this role requires strong problem-solving skills, adaptability, collaboration across global teams, and the ability to influence outcomes through data-driven recommendations.
This is an excellent opportunity for a technology professional who thrives in a structured, fast-paced environment, embraces innovation, and is passionate about building modern data capabilities that help transform both the client and employee experience.
What you have
Required Qualifications
- Bachelor’s degree in Computer Science, Information Technology, or a related technical field; Master’s degree preferred.
- 3+ years of data engineering, ETL development, or data integration experience.
- 3+ years of experience designing, developing, and supporting enterprise data pipelines.
- Strong experience with SQL and relational database technologies.
- Hands-on experience with Google Cloud Platform (GCP), including BigQuery, Cloud Storage, Dataflow, Composer, and Pub/Sub.
- Python development experience for data engineering and automation solutions.
- Experience developing and supporting ETL processes and enterprise data integration solutions, including Informatica Intelligent Cloud Services (IICS).
- Experience implementing data quality, validation, exception handling, and data governance best practices.
- Experience gathering, analyzing, and translating business requirements into technical solutions and source-to-target data mappings.
- Ability to design and optimize solutions for processing large volumes of structured and unstructured data.
- Experience working within Agile software development environments.
- Strong problem-solving, analytical, and decision-making skills.
- Demonstrated ability to collaborate effectively with cross-functional teams and communicate technical concepts to diverse audiences.
- Ability to mentor junior team members and contribute to team success.
- Commitment to continuous learning and adoption of emerging technologies.
Preferred Qualifications
- Experience supporting enterprise platforms such as Workday, BMC Remedy Helix, Jira, Rally, or similar business systems.
- Experience with DevOps and software delivery tools including GitHub, Bamboo, and Liquibase.
- Strong understanding of data architecture principles, development standards, and engineering best practices.
- Experience creating and maintaining source-to-target mapping documentation.
- Ability to identify operational challenges, recommend solutions, and drive process improvements.
- Strong written and verbal communication skills, including technical documentation.
- Experience working within highly collaborative, fast-paced, and evolving technology organizations.
In addition to the salary range, this role is eligible for bonus or incentive opportunities.