Business Analyst

Role Overview

We are seeking a Business Analyst to support a large‑scale data transformation program within the investment management and advisory domain. The role requires a strong functional understanding of investment data (public and private markets), combined with hands‑on data analysis capabilities, including source‑to‑target mapping and SQL‑based exploration. The analyst will act as a bridge between business stakeholders, data engineering teams, and platform architects to ensure accurate, high‑quality data delivery aligned with business needs.

• Collaborate with business stakeholders (investment teams, research, performance reporting, client reporting) to gather, analyze, and document data requirements
• Translate business requirements into detailed functional specifications, including source‑to‑target mappings (STTM) for data migration and transformation initiatives
• Analyze source systems and data structures to understand data lineage, quality issues, and transformation logic
• Write and execute SQL queries for data profiling, validation, reconciliation, and root cause analysis
• Work closely with data engineering teams (ETL/ELT, Snowflake/Databricks environments) to ensure correct implementation of business rules
• Support data quality initiatives by defining validation rules, reconciliation logic, and exception handling processes
• Participate in data model reviews, ensuring alignment with investment domain concepts such as portfolios, securities, benchmarks, transactions, and performance metrics
• Assist in UAT planning and execution, including test case creation, defect tracking, and validation of transformed datasets
• Contribute to data governance practices, including metadata documentation, data lineage tracking, and glossary definitions
• Engage in Agile ceremonies and provide continuous feedback to improve delivery outcomes

• Strong understanding of investment management domain concepts, including:
• Public markets (equities, fixed income)
• Private investments (PE, VC, real assets)
• Portfolio structures, holdings, transactions, benchmarks
• Performance and attribution concepts

• Proven experience in data transformation or data migration programs within financial services or asset management
• Hands‑on experience in creating source‑to‑target mappings and functional specifications for data pipelines
• Strong SQL skills for data analysis, including joins, aggregations, window functions, and data validation queries
• Experience working with modern data platforms such as Snowflake, Databricks, or similar cloud‑based ecosystems
• Familiarity with data warehousing concepts, dimensional modeling, and data lake architectures
• Strong analytical thinking and ability to interpret complex datasets and business rules
• Experience working in Agile delivery environments

• Exposure to tools/platforms commonly used in investment data ecosystems (e.g., Bloomberg, Fact Set, Aladdin, Burgiss, or similar)
• Understanding of data governance frameworks, including data quality, lineage, and stewardship
• Experience with ETL/ELT tools or orchestration frameworks (e.g., Airflow)
• Basic understanding of Python/PySpark for data analysis is a plus
• Prior experience in working with consulting firms or investment advisors is highly desirable

• Strong communication skills with the ability to interact with both business and technical teams
• Attention to detail, especially in data mapping and validation activities
• Problem‑solving mindset with the ability to identify data issues and propose solutions
• Ability to manage multiple priorities in a fast‑paced transformation environment