Technology Lead Python Data Engineer - Vice President

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)