Data Engineer w/ Python

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. Project Details:needs to modernize a large codebase of 700-800 legacy Perl scripts that interact with an Oracle database. You will assess, test, and redevelop these scripts to a more streamlined and testable solution using Python, dbt, and Apache Airflow. ### Key Responsibilities & Outcomes

• 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.
• Automate and streamline jobs and processes, integrating with an Oracle database using PL/SQL.

• Resume Constraint: Resumes MUST be 3 pages or less.
• 5+ years of Python development experience, with a strong understanding of system/process automation.
• Hands-on dbt & Oracle database experience is MANDATORY.
• Solid understanding of Oracle 19c database, SQL tuning, and PL/SQL concepts.
• 2+ years of Apache Airflow building production DAGs.
• Experience orchestrating jobs that move large volumes of data across enterprise systems.
• ETL background and experience with Python Shell Scripts.
• Advanced and fundamental Linux knowledge.
• 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.

Preferred:

• Prior experience modernizing legacy data workflows from Perl or PL/SQL stored procedures.
• Finance industry experience.
• 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.