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Job description
We’re seeking an experienced Python Developer to lead the automation and orchestration of complex data workflows. The ideal candidate will have hands-on experience designing robust, fault-tolerant, and auditable pipelines across on-prem Oracle systems, integrating with job schedulers like RunMyJobs, and modernizing legacy processes using Apache Airflow. You will play a critical role in replacing legacy Perl/PLSQL scheduling logic with modern, Python-based DAG orchestration while ensuring traceability, data quality, and recoverability., Develop, deploy, and maintain Python-based automation scripts to orchestrate jobs across Oracle 19c on-prem systems. Design and implement Airflow DAGs to manage complex interdependent ETL workflows. Migrate existing job logic from Perl, RunMyJob, and PL/SQL-based scheduling into modular, observable Airflow DAGs. Build custom Airflow operators/sensors for integration with Oracle, REST APIs, file drops (SFTP/FTP), and external triggers. Implement robust error handling, alerting and retry mechanisms across job pipelines. Collaborate with DBAs and application teams to understand job dependencies, critical paths, and data lineage. Establish job execution logs, audit trails, and SLA monitoring dashboards. Participate in code reviews, documentation, and onboarding new jobs into the orchestrator.
Requirements
Oracle database experience; Solid understanding of Oracle 19c database, SQL tuning, and PL/SQL concepts -Finance experience is nice to have -ETL background/Python Shell Script -5+ years of Python development experience, with strong understanding of system/process automation -Linux both advanced & fundamental -2+ years of Apache Airflow building production DAGs. -Experience orchestrating jobs that move large volumes of data across enterprise systems. -Familiarity with job schedulers (RunMyJob, Autosys, etc.) and how to replace/abstract them using orchestration tools. -Strong debugging skills across logs, databases, and filesystem for failed jobs or partial runs. -Experience building REST API integrations, SFTP/file movement logic, and parameter-driven automation. Project: -BBH needs to modernize a large codebase of 700-800 legacy Perl scripts that interact with an Oracle database. They are looking to move away from these legacy scripts to a more streamlined and testable solution and re-engineer with Python and Apache Airflow -Need to test the scripts and update them using Python and Airflow - must have strong Python and Apache Airflow -Assess the existing legacy Perl scripts and redevelop these scripts using Python and Apache Airflow -Automate and streamline jobs and processes -Integrate with an Oracle database using PL/SQL Torc Job Type, 5+ years of Python development experience, with strong understanding of system/process automation. 2+ years of Apache Airflow building production DAGs. Solid understanding of Oracle 19c database, SQL tuning, and PL/SQL concepts. Experience orchestrating jobs that move large volumes of data across enterprise systems. Familiarity with job schedulers (RunMyJob, Autosys, etc.) and how to replace/abstract them using orchestration tools. Strong debugging skills across logs, databases, and filesystem for failed jobs or partial runs. Experience building REST API integrations, SFTP/file movement logic, and parameter-driven automation. Bonus / Preferred Experience: Prior experience modernizing legacy data workflows from Perl or PL/SQL stored procs. Hands-on knowledge of Git/Bitbucket, Jenkins, CI/CD pipelines for code-controlled job rollouts. Familiarity with financial data models (e.g., holdings, transactions, NAVs, tax lots). Basic understanding of data governance, audit, and operational risk in financial systems.
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