Python Developer (W2 Only / No C2C) (Local Candidates Only)

TEKsystems•Jersey City, NJ

4d•$68 - $70•Hybrid

About The Position

Our client is seeking an experienced Senior Python Developer to join the Time Series Market Data team. This role focuses on building scalable systems that process large volumes of data and deliver reliable Python-based services in high-demand environments. The ideal candidate will design and implement robust solutions that empower business users and ensure system resiliency at scale.

Requirements

5-8 years of software development experience
5+ years of Python-focused development delivering scalable backend/data workflows
Proven experience designing systems for large-scale, high-volume environments
Hands-on experience building and operating ETL/data pipelines on distributed compute frameworks
Ability to work independently within complex, evolving market risk technology stacks
Hands-on development with enterprise Python platforms for ETL and application workflows
Familiarity with Quartz distributed compute grids and data processing frameworks
Ability to navigate proprietary stacks and quickly become productive in complex environments
Strong experience building scalable backend and data processing services
Proficient in core data structures and architectural upgrades
Expertise in implementing robust ETL pipelines
Designing services to handle stress, failure scenarios, and high-volume workloads
Diagnosing scale issues (contention, latency, throughput, resiliency) and implementing solutions
Comfortable discussing trade-offs, failure modes, observability, and performance tuning

Nice To Haves

Basic SQL proficiency (queries, schema familiarity)
Experience in market risk or enterprise banking environments
Exposure to service integration patterns, observability tooling, and performance engineering at scale

Responsibilities

Develop, enhance, and maintain ETL pipelines and backend services on Quartz using distributed computing grids and internal frameworks
Design systems for scalability, reliability, and fault tolerance
Upgrade architecture and optimize performance
Identify system bottlenecks and implement pragmatic solutions
Integrate data across risk systems via APIs and services, ensuring efficient movement of large datasets
Participate in technical interviews and design discussions, articulating approaches to resiliency and performance
Collaborate with partner teams on data pipeline standards and framework adoption
Drive operational excellence through monitoring, controls, error attribution, and automated remediation