Business Analyst

Role overview

This opportunity is for a Business Analyst to support a major data transformation initiative in the investment management and advisory space. The position calls for practical knowledge of investment data across public and private markets, along with strong hands-on analysis skills such as source-to-target mapping and SQL-driven investigation. In this role, you will connect business teams, data engineering groups, and platform architects to help deliver accurate, reliable data that matches business expectations.

Key responsibilities

• Work with stakeholders from investment, research, performance reporting, and client reporting teams to collect, analyze, and document data needs.
• Convert business needs into detailed functional documentation, including source-to-target mappings for migration and transformation work.
• Review source systems and data structures to understand lineage, quality gaps, and transformation rules.
• Develop and run SQL queries for profiling, validation, reconciliation, and root-cause analysis.
• Partner with data engineering teams working in ETL/ELT and Snowflake or Databricks environments to make sure business rules are implemented correctly.
• Support data quality efforts by defining validation logic, reconciliation checks, and exception handling approaches.
• Take part in data model reviews to ensure the design aligns with investment concepts such as portfolios, securities, benchmarks, transactions, and performance measures.
• Support UAT preparation and execution, including test case design, defect management, and verification of transformed data.
• Help maintain data governance practices through metadata records, lineage tracking, and glossary definitions.
• Participate in Agile ceremonies and share feedback that helps improve delivery results.

Requirements

• Strong working knowledge of investment management concepts, including public markets such as equities and fixed income, as well as private investments like private equity, venture capital, and real assets.
• Understanding of portfolio structures, holdings, transactions, benchmarks, performance, and attribution concepts.
• Demonstrated background in data transformation or data migration work within financial services or asset management.
• Hands-on experience preparing source-to-target mappings and functional specifications for data pipelines.
• Strong SQL capability for analysis, including joins, aggregations, window functions, and validation queries.
• Experience with cloud data platforms such as Snowflake or Databricks, or comparable environments.
• Familiarity with data warehousing, dimensional modeling, and data lake architectures.
• Strong analytical ability to interpret complex datasets and business rules.
• Experience working in Agile delivery environments.
• Exposure to investment data tools or platforms such as Bloomberg, FactSet, Aladdin, Burgiss, or similar solutions is preferred.
• Knowledge of data governance practices, including quality, lineage, and stewardship, is preferred.
• Experience with ETL/ELT tools or orchestration frameworks such as Airflow is preferred.
• Basic Python or PySpark knowledge is an advantage.
• Prior work with consulting firms or investment advisors is highly desirable.

Key competencies

• Clear communication skills for working effectively with both business and technical audiences.
• High attention to detail, especially during data mapping and validation tasks.
• Strong problem-solving approach with the ability to identify issues and recommend fixes.
• Ability to manage several priorities in a fast-moving transformation setting.

Additional information

This role is based in United, PA and is a full-time onsite position.

No stipend or salary amount was provided in the source information.