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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. Schwab Technology Services enables how clients manage their money by delivering innovative, reliable technology at scale. Within Schwab’s Google Cloud Data & Analytics ecosystem, this role plays a critical part in keeping enterprise data platforms running smoothly and reliably. As a Production Support Engineer, you’ll partner closely with data engineering, platform, and business teams to support cloud-based data workloads, strengthen operational health, and ensure data availability as enterprise demand continues to grow.
Job Responsibility:
Provide production and operations support for enterprise data and analytics workloads in a cloud-based environment
Monitor batch and streaming data jobs, identify failures or performance issues, and drive timely remediation
Support incident response, root cause analysis, and post-incident follow-ups to improve platform reliability
Maintain and enhance monitoring, alerting, and observability to proactively detect and prevent issues
Partner with data engineering and platform teams to support job onboarding, production readiness, and operational best practices
Execute standard operational activities including job restarts, data validations, and production hygiene
Contribute to operational runbooks, documentation, and continuous improvement of support processes
Support scheduling, dependency management, and workload coordination across enterprise data pipelines
Participate in on-call rotations and operational support coverage as required
Requirements:
Bachelor’s degree in computer science, engineering, or a related technical field, or equivalent practical experience
2–3 years of experience in a production support, operations, or reliability role within a data analytics, data engineering, or data warehouse environment
Hands-on experience with cloud-based data platforms and services, including GCP BigQuery, Airflow, Dataflow, and Pub/Sub
Hands-on experience supporting ETL or data pipeline workloads in production environments (IDMC or equivalent)
Strong SQL skills for data analysis, validation, and troubleshooting
Working knowledge of Python or other scripting languages for automation and operational optimization
Familiarity with CI/CD tools such as GitHub and related deployment workflows
Understanding of monitoring, alerting, and incident management practices in production systems
Nice to have:
Prior exposure to financial services or other regulated environments, including data governance and operational controls
Familiarity with automation and operational tooling to improve production efficiency and reduce manual effort
Experience with job scheduling and orchestration tools such as Control-M or Cloud Composer
What we offer:
401(k) with company match and Employee stock purchase plan
Paid time for vacation, volunteering, and 28-day sabbatical after every 5 years of service for eligible positions