Sr. Python Developer
Summary
Senior Python developer (5-6 years) on a Market Risk Technology team in Jersey City (5 days onsite), building and maintaining Python data pipelines and curated datasets that power daily risk analytics, with data-quality controls, CI/CD automation, Agile delivery, and production support.
Title : Sr. Python Developer with Market Risk
Location: Jersey City, NJ – 5 Days onsite Role
Duration: Fulltime
Role Description:
We are seeking a Senior Associate Developer (5–6 years’ experience) to join the Market Risk Technology team. You will design and build reliable Python-based data pipelines and curated datasets that support daily risk analytics. The role emphasizes hands-on delivery, data quality, performance, and collaboration with risk and business stakeholders, with ownership from planning through production and support.
Key Responsibilities:
- Design and implement Market Risk data pipelines in Python—from ingestion and transformation through delivery to analytics consumers.
- Own projects/features end-to-end: scope work, align with stakeholders, plan sprints, track progress, and deliver to SLAs.
- Apply data quality controls (validation, reconciliation, lineage) and monitor SLAs to ensure accuracy and timeliness.
- Improve performance and reliability of batch and near-real-time workflows through profiling and targeted optimization.
- Translate risk/business requirements into clear technical tasks and deliver features through Agile sprints.
- Automate routine workflows (packaging, testing, CI/CD, scheduling) and contribute to coding standards and reviews.
- Participate in production support, assist with incident resolution, and document fixes and runbooks.
- Create concise technical documentation, share knowledge with the team, and mentor junior engineers as needed.
Required Qualifications:
- Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
- 5–6 years of hands-on Python for data processing and automation (e.G., pandas;
packaging, testing). - Solid understanding of data modelling and ETL/ELT patterns;
experience building maintainable pipelines. - Experience implementing data quality checks and operational monitoring aligned to accuracy/timeliness goals.
- Proficiency with Git-based workflows and CI/CD;
familiarity with production change management. - Demonstrated ability to take ownership of a project or feature set, coordinate across teams, and deliver on time.
- Strong analytical and communication skills;
collaborative approach with risk and business stakeholders.