Engineer, Index Business Intelligence (Data Programming & Analytics)

Role Overview

Engineer, Index Business Intelligence (Data Programming & Analytics)

This role sits at the intersection of data engineering, business intelligence, and market analytics. You’ll transform large-scale datasets into structured, automated, and reusable reporting solutions that drive strategic and commercial decisions.

Responsibilities

• Own development, automation, and delivery of recurring index and business intelligence reporting (accuracy, consistency, timeliness)
• Build and maintain scalable data pipelines and automated workflows using Python, R, and SQL to reduce manual reporting
• Develop analytical products including:
  • dashboards
  • KPI scorecards
  • compliance summaries
  • client profiles
  • performance reports
• Create reusable, well-documented datasets to enable self-service analytics and consistent metric definitions
• Implement data quality frameworks (validation checks, anomaly detection, reconciliations, trend monitoring)
• Maintain documentation for data logic, transformations, assumptions, and metric definitions
• Translate ambiguous business questions into structured datasets, measurable KPIs, and technical solutions
• Communicate findings, constraints, and tradeoffs clearly to non-technical stakeholders
• Collaborate with cross-functional teams including Sales, Product, Finance, Research, and Legal

Requirements

• 5+ years experience in data engineering, analytics engineering, BI analytics, or advanced data analysis
• Strong proficiency in Python (especially pandas) and/or R, plus advanced SQL
• Experience working with large datasets and building scalable, repeatable data pipelines
• Proven experience automating reporting solutions and analytical workflows
• Strong analytical thinking and attention to detail; ability to resolve data inconsistencies independently
• Experience with data validation, transformation logic, and metric standardization
• Strong stakeholder collaboration skills and clear communication of technical concepts

Preferred

• Experience with regulatory/audit-related data frameworks, especially involving LLMs
• Familiarity with financial services, asset management, or regulatory reporting
• Exposure to international financial regulatory frameworks