Production Support Engineer
About The Position
Schwab Technology Services enables how clients manage their money by delivering innovative, reliable technology that expands access to investing and financial planning. Within this environment, Schwab’s Google Cloud Data & Analytics ecosystem powers firmwide insights across critical businesses including finance, risk, and brokerage—making data availability, reliability, and performance essential. As a Production Support Engineer within the Schwab Data organization, you will play a critical role in ensuring the stability and reliability of enterprise data platforms operating at scale in a cloud environment. This opportunity centers on maintaining the operational health of large-scale data pipelines and analytics services, where your ability to quickly diagnose issues, drive root cause resolution, and improve system resilience directly impacts business outcomes and decision-making. You will collaborate closely with data engineering, platform engineering, and business stakeholders to ensure production readiness, optimize operational processes, and continuously improve system performance as data complexity and demand grow. In this role, you will apply strong analytical thinking and problem-solving skills to monitor and support batch and streaming workloads, proactively identify risks, and enhance observability across the platform. You will contribute to building more efficient, automated, and scalable support processes while strengthening incident response practices and operational discipline. Your work will help ensure data integrity, availability, and trust across the enterprise while developing your expertise in cloud-based data ecosystems and modern data engineering operations.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
- 2–3+ years of experience in production support, operations, or reliability engineering within data analytics, data engineering, or data warehouse environments
- Hands-on experience with cloud-based data platforms and services (e.g., BigQuery, Dataflow, Pub/Sub, Airflow or equivalent)
- Experience supporting ETL or data pipeline workloads in production environments
- Strong SQL skills for data analysis, validation, and troubleshooting
- Working knowledge of Python or scripting languages for automation and operational efficiency
- Experience with job scheduling and orchestration tools (e.g., Control-M, Cloud Composer, or equivalent)
- Familiarity with CI/CD tools (e.g., GitHub) and deployment workflows
- Understanding of monitoring, alerting, and incident management practices in production systems
- Demonstrated ability to troubleshoot complex issues, perform root cause analysis, and drive resolution in a timely manner
Nice To Haves
- Experience working in financial services or regulated environments with exposure to data governance and operational controls
- Experience implementing automation or operational tooling to improve system efficiency and reduce manual intervention
- Exposure to cloud-based observability, monitoring, and reliability engineering practices at scale
- Experience collaborating across cross-functional engineering and business teams in a fast-paced environment
Responsibilities
- Ensuring the stability and reliability of enterprise data platforms operating at scale in a cloud environment.
- Maintaining the operational health of large-scale data pipelines and analytics services.
- Quickly diagnosing issues, driving root cause resolution, and improving system resilience.
- Collaborating closely with data engineering, platform engineering, and business stakeholders to ensure production readiness, optimize operational processes, and continuously improve system performance.
- Applying strong analytical thinking and problem-solving skills to monitor and support batch and streaming workloads.
- Proactively identifying risks and enhancing observability across the platform.
- Contributing to building more efficient, automated, and scalable support processes.
- Strengthening incident response practices and operational discipline.
- Ensuring data integrity, availability, and trust across the enterprise.
- Developing expertise in cloud-based data ecosystems and modern data engineering operations.
Benefits
- Bonus or incentive opportunities
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
