Senior Data Analytics Developer - Vice President

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Job Overview

The Vice President, Data Analytics Developer is a senior individual contributor role within Equities & Prime Services Technology, focused on designing, building, and maintaining high-quality data analytics applications and pipelines. This position requires deep hands-on engineering expertise, strong financial data domain knowledge, and the ability to partner closely with business stakeholders and quantitative analysts to deliver impactful analytics solutions.

Prime Services Technology provides business solutions to Prime Brokerage, Equity Finance, Delta One, Futures Execution and Clearing, and OTC Clearing businesses. The Data Analytics Developer will be a core member of the Prime Services Data team, responsible for developing analytics applications, data sourcing integrations, and data quality solutions — working collaboratively with other Markets teams that rely on Prime data.

The ideal candidate is a strong hands-on engineer with deep expertise in Python, complemented by solid knowledge of financial data across the trade lifecycle — including orders, executions, trade processing, and position management. Experience with Java is a strong plus given existing services built on the JVM stack. The candidate will thrive in an environment that requires close collaboration with business stakeholders, quantitative analysts, and technology teams, translating complex requirements into elegant, production-grade software solutions. As part of a global team spanning the US and UK, the candidate will also support production processes and batch jobs that run during Asia morning hours, ensuring operational stability and providing timely resolution.

Excellent communication skills are essential to work effectively with business leaders, quantitative analysts, and technology teams across Markets Technology.

Key Responsibilities

Hands-On Engineering & Development

• Design, develop, and maintain data analytics applications and pipelines with a primary focus on Python; leverage Java where applicable for existing services and integrations
• Actively leverage AI-assisted development tools (such as GitHub Copilot, Devin, and Claude) to accelerate engineering delivery, improve code quality, and drive innovation; contribute to the design and development of AI-powered monitoring agents that enhance operational visibility and automate routine production workflows
• Build and optimize data sourcing integrations to ingest data from multiple platforms within Prime Services and Markets Technology
• Develop analytics tools and dashboards that enable business users and quantitative analysts to derive actionable insights from financial data
• Write production-quality, well-tested, and maintainable code; participate in code reviews and uphold engineering best practices
• Architect scalable data solutions for processing large volumes of orders, executions, trades, and position data
• Implement and maintain batch processing jobs and automated workflows for data transformation and distribution
• Troubleshoot and resolve complex technical issues across the data platform stack
• Leverage modern data platform technologies — including data mesh architectures (Trino/Starburst), object storage (S3), distributed streaming (Kafka), and large-scale data processing (Spark) — to build performant, scalable solutions

Production Support & Global Operations

• Support production processes and batch jobs that run during Asia morning hours, ensuring timely execution and prompt issue resolution
• Coordinate with the global team across US and UK to ensure seamless handoffs and operational continuity
• Contribute to monitoring, alerting, and incident response procedures for critical data pipelines
• Drive root cause analysis and implement permanent fixes for production issues
• Contribute to operational resilience and business continuity for data-critical processes

Business Partnership & Requirements Gathering

• Work closely with key business SMEs and Quantitative Analysts to develop an in-depth understanding of their critical data and analytics needs
• Gather and translate complex business requirements into clear technical specifications and actionable engineering solutions
• Recognize patterns of data needs across multiple business requirements and address them through efficient, reusable solutions
• Partner with other Markets teams that need data from Prime Services to ensure seamless data sharing and collaboration
• Support the implementation of data visualization tools and platforms for analytics and reporting

Data Sourcing & Quality

• Contribute to data sourcing efforts to integrate data from multiple platforms within Prime Services and Markets Technology
• Ensure data accuracy, completeness, and timeliness across all analytics outputs
  Implement and monitor data quality rules, validation frameworks, and remediation processes
• Maintain metadata and data lineage documentation for analytics pipelines
• Adhere to enterprise data standards and regulatory requirements

Required Qualifications

Experience

• 8–10 years of experience in software engineering, data engineering, or data analytics within Banking or Financial Services
• Strong hands-on engineering background with a proven ability to design, build, and maintain production-grade data systems as an individual contributor
• Demonstrated experience using modern AI-assisted development and testing tools (e.g., GitHub Copilot, Devin, Claude, or equivalent) to improve engineering productivity and code quality; hands-on experience building or contributing to AI-powered agents — particularly for monitoring, alerting, or workflow automation — is strongly preferred
• Solid business knowledge of financial data, particularly in Markets — including orders, executions, trade processing, position management, and related trade lifecycle data; Prime Services / Prime Brokerage background is a plus
• Experience working directly with quantitative analysts and business stakeholders to translate requirements into technical solutions
• Experience supporting global production environments, including off-hours batch processing and operational support

Technical Skills

• Programming Languages: Strong hands-on proficiency in Python for building data pipelines, analytics tools, and production applications; knowledge of Java is a plus for working with existing JVM-based services
• Data Platforms (Plus): Familiarity with data mesh technologies such as Trino/Starburst, object storage (S3), distributed stream processing (Kafka), and large-scale data processing frameworks (Spark) is highly preferred
• AI Development & Tooling: Proficiency with modern AI-assisted coding and testing tools (GitHub Copilot, Devin, Claude, or equivalent); practical experience designing and building LLM-powered or agentic solutions for operational use cases such as monitoring and alerting
• Data Integration: Solid knowledge of data ingestion and distribution frameworks, both enterprise and open-source
• Financial Data Domain: Strong understanding of markets financial data — orders, executions, trade processing, position management, P&L, risk, and reference data
• Distributed Systems: Experience with distributed messaging systems such as Kafka and distributed caching services such as Gemfire/Redis
• Database Technologies: Proficient in SQL and various database management systems (relational and NoSQL)
• Batch Processing: Experience designing and managing batch jobs, schedulers, and workflow orchestration tools
• Data Quality: Experience with data quality frameworks, validation techniques, and remediation strategies
• DevOps & CI/CD: Familiarity with CI/CD pipelines, containerization, and deployment automation
• Data Platform Architecture: Experience building and maintaining data lakes, data warehouses, and analytics platforms (on-premises and/or cloud) is preferred
• Data Visualization: Experience implementing data visualization tools and platforms for analytics and reporting is a plus

Communication & Interpersonal Skills

• Excellent verbal and written communication skills with the ability to articulate technical concepts to business and executive audiences
• Strong ability to work with quantitative analysts and business SMEs to understand complex data requirements
• Demonstrated ability to interact and work effectively with diverse, globally distributed teams
• Ability to work under pressure, facilitate discussions, and contribute constructively to group meetings
• Strong diplomacy skills required to exchange complex information across business and technology stakeholders

Education

• Bachelor's/University degree or equivalent experience, preferably in Computer Science, Information Systems, Mathematics, Statistics, Engineering, or a related quantitative field
• Master's degree or advanced certifications in relevant fields preferred

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