Data Engineering Senior Lead Analyst - Senior Vice President

• Conducts strategic data analysis, identifies insights and implications and make strategic recommendations, develops data displays that clearly communicate complex analysis
• Mines and analyzes data from various banking platforms to drive optimization and improve data quality
• Deliver analytics initiatives to address business problems with the ability to identify data required, assess time & effort required and establish a project plan
• Consults with business clients to determine system functional specifications
• Applies comprehensive understanding of how multiple areas collectively integrate to contribute towards achieving business objectives
• Consults with users and clients to solve complex system issues/problems through in-depth evaluation of business processes, systems and industry standards
• recommends solutions
• Leads system change process from requirements through implementation
• provides user and operational support of application to business users
• Formulates and defines systems scope and goals for complex projects through research and fact-finding combined with an understanding of applicable business systems and industry standards
• Impacts the business directly by ensuring the quality of work provided by self and others
• impacts own team and closely related work teams
• Considers the business implications of the application of technology to the current business environment
• identifies and communicates risks and impacts
• Drives communication between business leaders and IT
• exhibits sound and comprehensive communication and diplomacy skills to exchange complex information
• Performs other duties and functions as assigned
• Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency

• 10+ years of hands-on professional software engineering experience, including designing and delivering distributed systems, microservices, and full-stack applications in complex enterprise environments
• Proficiency in programming in Python, JavaScript/TypeScript (React or Angular) is mandatory
• Experience of using cloud services such as AWS and distributed systems such as Kubernetes, Kafka, S3, Databases like DynamoDB, MongoDB or any other NoSQL database in addition to classical RDBMS such as PostgreSQL, Oracle etc
• Experience of following TDD and passionate about clean code principles
• Solid understanding of GenAI principles and architectures, coupled with proficiency in frameworks and libraries (e.g., TensorFlow, PyTorch, Hugging Face Transformers) and MLOps practices for managing the lifecycle of GenAI solutions
• Strong background in GenAI, including working with LLMs, Google Gemini, and vector databases (e.g. pg_vector)
• experience in designing retrieval-augmented solutions is highly preferred
• Solid understanding and experience of using data structures, algorithms and SQL
• Able to independently work in fast paced and rapidly changing environment
• Product Management Skills: Business Acumen / Roadmaps / Prioritization: Ability to collaborate with multiple stakeholders across the organization is vital. You must be able to connect technical decisions to business outcomes. This includes understanding your product's P&L, customer acquisition costs, and lifetime value. You should be adept at creating outcome-oriented roadmaps that align with business objectives, not just a list of features. This involves using sophisticated prioritization frameworks to justify your decisions with data and strategic reasoning
• Technical Translation: Able to translate complex technical concepts into clear, concise language for non-technical audiences, and similarly, translate business requirements into technical specifications for your engineering team
• Understanding the Tech Stack: You need a deep familiarity with your product's tech stack. This allows you to have credible conversations about technical debt, refactoring, and the feasibility of new features
• Security & Compliance: A solid understanding of security best practices and relevant compliance standards (like CPRA, GDPR, etc.) is crucial, as you are responsible for ensuring your product is secure and compliant
• System Design & Architecture: You must be able to engage in technical discussions about system architecture. This includes understanding the trade-offs of different approaches (e.g., micro services vs. monolith, REST)
• Data-Driven Decision Making: Expert at performing cohort analysis using SQL to query databases directly. You must be able to define the right KPIs and connect them to broader business goals
• Bachelor’s/University degree or equivalent experience

Master's degree preferred