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About the Role
As a Cloud Data Platform Engineer at Schwab, you will play a critical role in advancing Schwab's Google Cloud-based data ecosystem. You will support platforms that power enterprise analytics, regulatory reporting, operational intelligence, and AI-driven capabilities. This role involves engineering, administering, and optimizing large-scale cloud data platforms, collaborating with various teams to improve reliability, scalability, automation, performance, and cost efficiency. Success requires strong cloud platform expertise, a commitment to operational excellence, and the ability to solve complex technical challenges.
Responsibilities
- Engineer, administer, and optimize large-scale cloud data platforms supporting petabytes of data and thousands of users.
- Collaborate with platform engineering, security, architecture, governance, and business teams.
- Improve reliability, scalability, automation, performance, and cost efficiency of cloud data platforms.
- Drive secure, resilient, and innovative data solutions that enable business outcomes.
Requirements
- 7+ years of experience supporting, engineering, or administering enterprise-scale cloud data platforms.
- Hands-on experience with Google Cloud services including BigQuery, Cloud Composer, Cloud Run, Cloud Storage, Cloud Functions, and Dataflow.
- Strong knowledge of IAM, VPC Service Controls, and BigQuery security best practices, including dataset-level access controls, column-level security, and data masking.
- Experience managing the full lifecycle of cloud services, including provisioning, monitoring, scaling, optimization, and decommissioning.
- Experience with Terraform or comparable Infrastructure-as-Code (IaC) tools.
- Experience implementing and supporting CI/CD automation using GitHub Actions, Liquibase, or similar technologies.
- Advanced Python scripting experience used to automate operational workflows and platform administration.
- Strong proficiency with SQL performance tuning and query optimization in large-scale data environments.
- Experience building operational dashboards and reporting solutions using Tableau, Power BI, or comparable reporting tools.
- Experience with incident management and ticketing platforms such as Jira, Remedy, or equivalent solutions.
- Proven ability to lead technical initiatives, influence stakeholders, and collaborate effectively across cross-functional teams.
- Experience supporting enterprise data warehouse platforms operating at large scale.
- Experience improving platform resiliency, disaster recovery readiness, and operational governance.
- Strong analytical and strategic problem-solving capabilities.
- Experience evaluating emerging cloud technologies and leading proof-of-concept initiatives.
- Demonstrated ability to mentor engineers and provide technical leadership.
- Strong written and verbal communication skills with the ability to influence diverse stakeholders.
- Experience driving operational excellence, automation, and continuous improvement initiatives.
- Financial services or highly regulated industry experience is a plus.
Skills
- Google Cloud services (BigQuery, Cloud Composer, Cloud Run, Cloud Storage, Cloud Functions, Dataflow)
- IAM
- VPC Service Controls
- BigQuery security best practices
- Terraform
- Infrastructure-as-Code (IaC)
- CI/CD automation (GitHub Actions, Liquibase)
- Python scripting
- SQL performance tuning
- SQL query optimization
- Tableau
- Power BI
- Jira
- Remedy
Location
- On-site
Work Type
- On-site
- Full-time
Experience Level
- 7+ years of experience supporting, engineering, or administering enterprise-scale cloud data platforms
Salary/Compensations
- Eligible for bonus or incentive opportunities
About the Company
- At Schwab, you’re empowered to make an impact on your career.
- Innovative thought meets creative problem solving, helping us challenge the status quo and transform the finance industry together.
- Schwab Technology Services enables the future of how clients manage their money by delivering innovative and reliable technology solutions that support investing, financial planning, and enterprise-scale decision making.