Jobs · New Jersey

Python Developer

Marchon Partners · Jersey City, NJ · 1 mo ago
HybridContract

About the role

Python Developer position in Jersey City, Contract‑to‑Hire with an initial 6+ month contract, start ASAP. Interview process includes video and onsite interviews.

Responsibilities

  • 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.

Skills

  • 5+ years of Python development experience, with strong understanding of system/process automation.
  • Experience with DBT (bonus/preferred).
  • 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.
  • Prior experience modernizing legacy data workflows from Perl or PL/SQL stored procedures.
  • 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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