Django Developer Jobs

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2d ago

Technology Lead Python Data Engineer - Vice President

Citi Rutherford, NJ

Rutherford, NJ

2d ago

$142k - $213k/yr Full time Backend Developer Manager Python

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Job Description

The Technology Lead Python Data Engineer role at Citi focuses on building modern, scalable Python-based platforms that support credit risk management. This position blends hands-on engineering with system architecture, technical leadership, and AI-enabled innovation, with an emphasis on microservices, cloud-native design, and enterprise governance.

Location and Employment Details

Location: Rutherford, NJ, United States (onsite)
Time type: Full time
Primary location: Rutherford New Jersey, United States
Job family group: Technology
Job family: Applications Development
Salary range: USD 142,320 - 213,480 per yearly
Anticipated posting close date: Sep 04, 2026

Role Summary

As a Technology Lead Python Data Engineer, you will lead the design and development of platforms for credit risk analytics, workflows, and reporting. The role requires architecture and delivery of Python-based applications, collaboration with risk and product stakeholders, and technical leadership across engineering standards and microservices design.

Responsibilities

Architect, design, and deliver scalable, Python-based applications supporting credit risk analytics, workflows, and reporting.
Partner with risk, product, and technology leadership to integrate platforms, identify enhancements, and enable new products and process improvements.
Resolve high-impact, complex initiatives using deep analysis of business processes, system flows, and industry standards.
Ensure solutions align with enterprise architecture, data, security, and infrastructure blueprints.
Establish and enforce engineering standards for coding, testing, CI/CD, debugging, and production readiness.
Design and evolve microservices-based architectures with scalability, resiliency, observability, and maintainability in mind.
Apply AI and GenAI capabilities to modernize workflows, automate analysis, and surface new credit risk insights.
Act as a technical leader and mentor, coaching mid-level engineers and analysts and allocating work as needed.
Use sound risk and control judgment to meet compliance expectations with laws, regulations, and policies while safeguarding clients, data, and the firm.

Required Experience and Qualifications

Experience: 6+ years in application development or systems engineering within complex environments.
Advanced proficiency in Python and SQL, with strong software engineering fundamentals.
Hands-on experience building API-driven services using FastAPI, Pydantic, and/or Django.
Proven expertise designing and implementing microservices architectures, including service decomposition, inter-service communication, resiliency patterns, and observability.
Strong experience with Docker and Kubernetes, deploying and operating containerized services in production.
Deep understanding of system architecture, data flows, and distributed systems.
Experience working in Linux, including shell scripting and operational troubleshooting.
Track record implementing unit testing, TDD, and automated quality controls.
Subject Matter Expert (SME) in at least one application, platform, or service domain.
Working knowledge of large language models (LLMs) and modern AI platforms from leading providers such as OpenAI, Anthropic, Google, and Meta.
Experience designing or contributing to LLM-enabled solutions (e.g., copilots, workflow automation, analytics augmentation).
Familiarity with prompt engineering, model integration patterns, and AI governance considerations in enterprise environments.
Exposure to AI-assisted “vibe coding” practices using AI tooling to accelerate development and experimentation while maintaining engineering rigor.

Education

Bachelor’s degree (or equivalent experience) in Computer Science, Engineering, Mathematics, or a related STEM field.

Technology Focus

Python, SQL
FastAPI, Pydantic, Django
Microservices
Docker, Kubernetes
Linux, shell scripting
Unit testing, TDD
LLMs, OpenAI, Anthropic, Google, Meta, prompt engineering

Additional Skills / Bonus Differentiators

Experience with distributed data and compute platforms (e.g., Spark, PySpark, Hadoop, Hive).
Hands-on experience with graph databases, particularly Neo4j, for network, relationship, or dependency-driven use cases.
Background in credit risk, financial risk management, or banking platforms.
Experience modernizing or decomposing legacy monolithic systems in large enterprises.
Proven delivery of GenAI / AI-driven solutions in regulated or large-scale environments.

Benefits

Medical, dental & vision coverage
401(k)
Life, accident, and disability insurance
Wellness programs
Planned time off (vacation)
Unplanned time off (sick leave)
Paid holidays
Discretionary and formulaic incentive and retention awards (for eligible employees)

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