Overview Lead the automation and orchestration of complex data workflows using Python. Design, develop, and maintain robust, fault-tolerant, and auditable data pipelines across on-prem Oracle systems. Modernize and migrate legacy scheduling logic (Perl/PLSQL/RunMyJobs) to Python-based Apache Airflow DAGs. Integrate with job schedulers (RunMyJobs, Autosys, etc.) and create modular, observable workflows. Build and deploy custom Airflow operators/sensors for Oracle, REST API integrations, file transfers (SFTP/FTP), and external triggers. Ensure traceability, data quality, and recoverability in all automated processes. Implement strong error handling, alerting, retry, and monitoring mechanisms for production jobs. Collaborate with DBAs and application teams to analyze job dependencies, critical paths, and data lineage. Establish and maintain job execution logs, audit trails, and SLA monitoring dashboards. Participate in code reviews, documentation, and onboarding of new jobs to the orchestration platform. Apply knowledge of Oracle 19c, SQL/PLSQL, and REST API integration to support enterprise data movement. Utilize CI/CD tools (Git/Bitbucket, Jenkins) for version control and automated deployment. Contribute to the modernization of data workflows, with attention to data governance and operational risk, especially in financial systems. Seniority level Entry level Employment type Full-time Job function Engineering and Information Technology Industries Information Services #J-18808-Ljbffr Largeton Group
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