Data & Integration Ops Engineer
$110,000–$130,000 year
HybridSt. Louis, Missouri, United States
Job Summary
Oversee end-to-end data pipeline operations across development, UAT, and production environments, monitoring Airflow DAGs to ensure on-time data delivery and SLA compliance. Troubleshoot integration workflows in Azure services including Logic Apps and Event Hub, diagnosing failures and coordinating recovery with Infrastructure and Cyber teams. Act as the primary incident responder during business hours, leading root cause analysis and implementing preventive measures to minimize disruptions. Manage production data governance by administering Snowflake RBAC, auditing write-access permissions, and enforcing security policies. Collaborate with data engineers to facilitate deployments of dbt models and pipeline code, conducting code reviews and refining CI/CD processes using GitHub Actions. Optimize pipeline performance through query tuning and resource scaling while implementing monitoring and alerting systems to detect anomalies proactively.
Required Qualifications
- Bachelor's degree in Computer Science, Software Engineering, or a related technical field, or equivalent hands-on experience
- Typically 5+ years of professional experience in data engineering, data operations (DataOps), or a related field
- Substantial experience managing production data pipelines and platforms
- Experience applying DevOps, DataOps, or SRE practices to production data systems
- Experience with cloud integration platforms (e.g., Azure Integration Services, MuleSoft, Boomi)
- Proven track record of operational excellence in a data-focused environment
- Familiarity with industry best practices in DataOps/Data Engineering and data governance standards
- Demonstrated ability to work independently, manage priorities, and take ownership of data products from design through ongoing support
- Strong hands-on experience with data workflow management systems (especially Apache Airflow/Astro for DAG orchestration)
- Familiarity with scheduling, monitoring, and maintaining complex DAGs in production
- Proficiency with SQL and data transformation frameworks like dbt (Data Build Tool)
- Capability to debug SQL queries and pipeline scripts to resolve data quality or performance issues
- Advanced programming skills in Python (or similar languages) for writing data pipeline jobs and automation scripts
- Experience with version control (e.g., Git) and understanding of CI/CD tools/processes for deploying data pipelines and platform changes
- Experience implementing monitoring and alerting systems (using tools such as logging frameworks, observability dashboards)
- Skilled in systematic troubleshooting and root cause analysis for complex systems under pressure
- Solid understanding of Snowflake (RBAC, secure views, dynamic tables, resource monitors)
- Strong working knowledge of Azure services relevant to data and integration pipelines (networking basics, APIM, Event Hub, AKS, Logic Apps)
- Excellent problem-solving abilities
- Strong communication skills to coordinate across engineering, analytics, and operations teams
- Demonstrated ability to document processes, produce runbooks, and clearly communicate during incident management
- This is a hybrid role with 3 days/week onsite in St. Louis
Desired Qualifications
- Experience applying DevOps, DataOps, or SRE practices to production data systems is highly desirable
- Experience with cloud integration platforms (e.g., Azure Integration Services, MuleSoft, Boomi) is a plus
- Experience in financial services, wealth management, or other regulated industries is a plus
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