Sr. Data Analytics Developer - VP - Hybrid

Description

This senior individual contributor role sits in the equities and prime services technology group, where you will design, build and maintain analytics applications and data pipelines. It needs strong engineering skills, solid financial data knowledge, and close work with business stakeholders and quantitative analysts.

The group builds technology for prime brokerage, equity finance, Delta One, futures execution and clearing, and OTC clearing. You will join the prime services data team and work with other markets teams that depend on prime data.

The company is looking for an engineer who is strong in Python and understands financial data across the trade lifecycle, including orders, executions, trade processing and position management. Java is a strong plus because some services run on the JVM. The team spans the US and UK, and you will also support production processes and batch jobs that run during Asia morning hours.

Strong communication is essential when working with business leaders, quant analysts and technology teams.

Responsibilities

• Build and maintain data analytics applications and pipelines, mainly in Python, and use Java where existing services and integrations require it.
• Use AI-assisted development tools such as GitHub Copilot, Devin and Claude to speed up delivery and improve code quality.
• Help design and build AI-powered monitoring agents that improve operational visibility and automate routine production tasks.
• Build data sourcing integrations that pull from multiple platforms across Prime Services and Markets Technology.
• Build analytics tools and dashboards so business users and quant analysts can act on financial data.
• Write production-grade, well-tested, maintainable code, take part in code reviews and apply engineering best practices.
• Design scalable solutions for large volumes of orders, executions, trades and positions.
• Build and run batch jobs and automated workflows for data transformation and distribution.
• Diagnose and resolve complex issues across the data platform stack.
• Use modern platform technologies, including Trino/Starburst data mesh, S3 object storage, Kafka streaming and Spark, to build fast, scalable systems.
• Run production processes and batch jobs during Asia morning hours, keeping them on time and resolving issues quickly.
• Coordinate with colleagues in the US and UK so handoffs are smooth and operations continue without gaps.
• Help set up monitoring, alerting and incident response for critical data pipelines.
• Lead root cause analysis and deliver permanent fixes for production problems.
• Support operational resilience and business continuity for data-critical processes.
• Work with key business SMEs and quant analysts to understand their critical data and analytics needs.
• Turn complex business requirements into clear technical specifications and practical engineering solutions.
• Spot shared data needs across multiple requests and meet them with efficient, reusable solutions.
• Work with other markets teams that need prime data so data sharing stays seamless.
• Help implement data visualization tools and platforms for analytics and reporting.
• Help with data sourcing across Prime Services and Markets Technology.
• Keep analytics outputs accurate, complete and timely.
• Implement and monitor data quality rules, validation frameworks and remediation processes.
• Maintain metadata and data lineage documentation for analytics pipelines.
• Follow enterprise data standards and regulatory requirements.

Requirements

• 8, 10 years of experience in software engineering, data engineering or data analytics within banking or financial services.
• A record of building and maintaining production data systems as an individual contributor.
• Hands-on experience with AI-assisted development and testing tools such as GitHub Copilot, Devin, Claude or equivalent, used to improve productivity and code quality.
• Practical experience designing and building LLM-powered or agentic solutions for operational use cases such as monitoring and alerting.
• Strongly preferred: hands-on experience building or contributing to AI-powered agents, particularly for monitoring, alerting or workflow automation.
• Solid knowledge of markets financial data, including orders, executions, trade processing, position management and related trade lifecycle data.
• Strong understanding of markets data including P&L, risk and reference data.
• Plus: a prime services or prime brokerage background.
• Hands-on experience working with quant analysts and business stakeholders, turning their requirements into technical solutions.
• Experience supporting global production environments, including off-hours batch processing and operational support.
• Strong hands-on Python for data pipelines, analytics tools and production applications.
• Plus: knowledge of Java for working with existing JVM-based services.
• Highly preferred: familiarity with Trino/Starburst, S3 object storage, Kafka and Spark.
• Solid knowledge of data ingestion and distribution frameworks, both enterprise and open-source.
• Experience with Kafka and distributed caching such as Gemfire or Redis.
• Proficiency in SQL and in relational and NoSQL database management systems.
• Experience designing and managing batch jobs, schedulers and workflow orchestration tools.
• Experience with data quality frameworks, validation techniques and remediation strategies.
• Familiarity with CI/CD pipelines, containerization and deployment automation.
• Preferred: experience building and maintaining data lakes, data warehouses and analytics platforms, on-premises and/or cloud.
• Plus: experience implementing data visualization tools and platforms for analytics and reporting.
• Excellent verbal and written communication, with the ability to explain technical concepts to business and executive audiences.
• Ability to work with quant analysts and business SMEs to understand complex data requirements.
• Ability to work effectively with diverse, globally distributed teams.
• Ability to work under pressure, lead discussions and contribute constructively in group meetings.
• Strong diplomacy for exchanging complex information between business and technology stakeholders.
• A bachelor's degree or equivalent experience. A degree in computer science, information systems, mathematics, statistics, engineering or a related quantitative field is preferred.
• Master's degree or advanced certifications in relevant fields are preferred.

Conditions

Full-time, hybrid role based in Tampa, Florida, United States.

Base salary range is $113,840.00 to $170,760.00.

Eligible employees may also receive discretionary and formulaic incentive and retention awards.

Anticipated posting close date is Oct 20, 2026.

Automated processing and AI are used to match skills to roles, but people conduct, check and make all hiring decisions.

Benefits

• Medical, dental and vision coverage.
• 401(k) plan.
• Life, accident and disability insurance.
• Wellness programs.
• Paid vacation, sick leave and paid holidays.
• Offerings may vary by jurisdiction, job level and date of hire.