Citi
Credit Risk Technology
TechnologyLeadPythonDataEngineer
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“Technology Lead Python Data Engineer at Citi. Skills: Python, Data Engineering, Microservices, AI. Architect, design, and deliver scalable, Python-based applications. Partner with risk, product, and technology leadership”
What You'll Achieve.
Build systems that shape credit decisions—at scale; Drive real-world financial impact; Deliver mission-critical platforms; Deliver systems that are performant, resilient, and compliant; Enable new products and process improvements
Industry & Context.
Deep analysis of business processes; System flows; Industry standards
What They're Looking For.
Must Have
10–15 years of experience in application development or systems engineering within complex environments., Advanced proficiency in Python and SQL, with 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., 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 environments, 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., Bachelor’s degree (or equivalent experience) in Computer Science, Engineering, Mathematics, or a related STEM field.
Nice to Have
Master’s degree preferred., 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.
What You'll Do.
Python-based applications
and technology leadership
Ensure solutions adhere to enterprise architecture
Establish and enforce engineering standards
Design and evolve microservices-based architectures
Apply AI and GenAI capabilities
Serve as technical leader and mentor
Apply sound risk and control judgment
How You'll Work.
Team & Collaboration
Partnering closely with risk, data, and platform teams; Partner with risk, product, and technology leadership; Coaching mid-level engineers and analysts
Full Job Description
## Discover Your Future in Credit Risk Technology Build systems that shape credit decisions—at scale. Join a fast‑moving Credit Risk Technology team where modern engineering, data, and AI come together to drive real‑world financial impact. We operate with a startup mindset—ownership, speed, and experimentation—within the rigor and responsibility of a global financial institution. You’ll help design and deliver mission‑critical platforms that support credit risk assessment, analytics, and decisioning across the firm. ## ## Job Overview The Technology Lead Python Data Engineer**** is a senior engineering leadership role focused on building and evolving modern, scalable platforms for credit risk management. You will lead application design and development while partnering closely with risk, data, and platform teams to deliver systems that are performant, resilient, and compliant. This role blends hands‑on development, system architecture, technical leadership, and AI‑enabled innovation, with a strong emphasis on microservices, cloud‑native design, and enterprise‑grade governance. ## ## Key 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 through deep analysis of business processes, system flows, and industry standards. * Ensure solutions adhere to 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, ensuring scalability, resiliency, observability, and maintainability. * Apply AI and GenAI capabilities to modernize workflows, automate analysis, and unlock new insights in credit risk. * Serve as techni
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