Production Support Data Engineer
- Southlake, TX, United States
- Austin, TX, United States
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Original job description
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 Technology Services enables the future of how clients manage their money by delivering innovative, reliable technology products and services at scale. As a Production Support Data Engineer supporting Schwab’s cloud data and analytics ecosystem, you will lead the operational support of enterprise data platforms, large-scale batch workloads, and business-critical data applications.
Combining hands-on technical expertise with strong production support ownership, you will anticipate, troubleshoot, and resolve production issues while improving automation, platform resilience, and operational stability. You will drive production readiness, releases, incident resolution, and operational change, collaborating across data engineering, platform, business, and external teams to strengthen data availability and service reliability. You will establish scalable support standards, enhance monitoring and preventive controls, communicate clearly during service disruptions, and continuously improve processes to deliver secure, stable, and reliable enterprise data operations.
This position requires participation in a scheduled on-call rotation, including occasional evenings, weekends, and holidays, to support production environments and respond to critical incidents.
What you have
Required Qualifications
- 7+ years of hands-on production support experience in a data warehousing environment.
- 3+ years of hands-on experience supporting ETL workloads; Informatica IDMC or IICS experience is highly preferred.
- 3+ years of experience supporting data and analytics applications in Google BigQuery, preferably GCP or a similar cloud data platform.
- Experience with Splunk, Remedy, Jira, or equivalent support tools.
- Demonstrated ability to lead production support for enterprise data platforms, applying analytical thinking and technical troubleshooting to identify root causes and restore service.
- Experience establishing operational standards, documentation, and support processes aligned with enterprise policies.
- Ability to improve data classification, storage, security, quality, and compliance through scalable technical solutions.
- Experience using data analysis and quality assurance practices to support informed decision-making, operational performance, and product integrity.
- Proven ability to communicate clearly and promptly during production incidents, coordinate cross-functional resolution efforts, and engage stakeholders through complex technical issues.
- Demonstrated technical leadership, including coaching team members, setting priorities, and supporting reliable delivery in a production environment.
- Bachelor’s degree in computer science, engineering, or a related field.
Preferred Qualifications
- 5+ years of experience with Control-M or AutoSys workload scheduling.
- Experience with Google Cloud data-processing services such as Airflow and Pub/Sub.
- Hands-on proficiency with Linux, shell scripting, SQL, and data analysis.
- Experience improving large-scale batch operations through automation, self-healing solutions, and continuous process improvement.
- Experience navigating incident and change management processes with an end-to-end understanding of system flows and the broader technology landscape.
In addition to the salary range, this role is eligible for bonus or incentive opportunities.
More about this job
Skills
- Troubleshoot
- Data engineering
- Improve business processes
- Data warehousing
- Informatica
- BigQuery
- Google Cloud
- Splunk
- Jira
- Analytical skills
- Troubleshooting
- Documentation
- Regulatory compliance
- Data analysis
- Quality assurance
- Decision making
- Leadership
- Coaching
- Computer science
- Scheduling
- Process data
- Apache Airflow
- Linux
- SQL
- Process improvement
- Change management