Application Development Lead (Bigdata & Analytics) - Vice President

1. Strategic Technology Roadmap & Architecture Define and Execute Vision: Establish and drive the strategic technology architecture roadmap for the Client Financials portfolio, ensuring alignment with long-term business outcomes. Technical Direction: Provide strategic direction and critical input into key technology decisions to ensure a scalable, robust, and future-proof buildout. Solution Design: Demonstrate deep technical acumen to collaborate with and direct a strong engineering team in making critical architectural and design decisions. 2. Cloud Transformation & Data Engineering Cloud-Native Engineering: Lead the design, development, and scaling of enterprise-grade, cloud-native data services on AWS. Databricks & Spark Migration: Drive the migration of legacy data platforms to Databricks, delivering high-performance Spark and PySpark solutions. Platform Optimization: Optimize system performance, capacity, and infrastructure efficiency to support data-heavy, high-throughput applications. AI-Enabled Analytics: Deliver AI-enabled operational and analytics platforms to unlock advanced insights and predictive capabilities. 3. Stakeholder Management & Business Alignment Methodology Representation: Present and represent the firm's client returns methodology to senior stakeholders across diverse business and technology teams, including Markets, Finance, Risk, Banking, Performance Management, and ICM. Impact Analysis: Clearly articulate and present the technology platform's impacts on revenue, expense, GSIB (Global Systemically Important Banks), and tax calculations. Relationship Building: Foster strong, collaborative partnerships with senior business and technology leaders to align engineering delivery with business priorities. 4. Engineering Leadership & Agile Delivery End-to-End Accountability: Take full and direct accountability for the solution delivery lifecycle of the Client Financials portfolio.

Leadership: Lead, mentor, and scale a high-performing team of expert data and software engineers, fostering a culture of technical excellence, quality, and velocity. Agile Execution: Drive agile execution across multiple complex data engines, calculation engines, and multi-dimensional analytics platforms. Qualifications & Experience Experience & Leadership 10+years of Proven Experience: Extensive background in software engineering and applications development, with a proven track record of owning and delivering large-scale application portfolios for complex business functions. Enterprise Scale: Demonstrated success in building, scaling, and optimizing enterprise data services and driving large-scale cloud transformation initiatives. Strategic Influence: Proven ability to influence technology strategy and build strong relationships with senior business and technology partners. Technical Expertise This individual possesses a robust technical background with deep expertise in cloud-native, Big Data, and analytics platforms, essential for driving complex financial solutions. Cloud & Big Data Platforms:  Deep expertise in AWS cloud-native architecture, coupled with strong hands-on and architectural experience in Databricks, Apache Spark, and PySpark. Proficient in the entire Hadoop ecosystem (HDFS, Hive, Sqoop) for Big Data environments. Database & Analytics:  Solid exposure to SQL Server and Oracle databases, with strong skills in query writing for data validation and manipulation. Proven experience in building high-performance calculation engines and multi-dimensional analytics platforms, including complex calculations. Tools & Practices:  Skilled with Git for version control; experienced with JIRA and Confluence for project management. Familiarity with DevOps practices and CI/CD pipelines is also present. Reporting & Emerging Tech:  Some exposure to Tableau for BI reporting. Familiarity with AI/ML-enabled operational and analytics platforms is highly desirable. Communication &