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.

Key Responsibilities

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• Collaborate with business stakeholders (investment teams, research, performance reporting, client reporting) to gather, analyze, and document data requirements.

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• Translate business requirements into detailed functional specifications, including source-to-target mappings (STTM) for data migration and transformation initiatives.

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• Analyze source systems and data structures to understand data lineage, quality issues, and transformation logic.

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• Write and execute SQL queries for data profiling, validation, reconciliation, and root cause analysis.

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• Work closely with data engineering teams (ETL/ELT, Snowflake/Databricks environments) to ensure correct implementation of business rules.

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• Support data quality initiatives by defining validation rules, reconciliation logic, and exception handling processes.

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• Participate in data model reviews, ensuring alignment with investment domain concepts such as portfolios, securities, benchmarks, transactions, and performance metrics.

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• Assist in UAT planning and execution, including test case creation, defect tracking, and validation of transformed datasets.

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• Contribute to data governance practices, including metadata documentation, data lineage tracking, and glossary definitions.

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• Engage in Agile ceremonies and provide continuous feedback to improve delivery outcomes.

Required Skills And Experience

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• Strong understanding of investment management domain concepts, including:

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• Public markets (equities, fixed income)

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• Private investments (PE, VC, real assets)

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• Portfolio structures, holdings, transactions, benchmarks

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• Performance and attribution concepts

Other Experiences

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• Proven experience in data transformation or data migration programs within financial services or asset management.

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• Hands-on experience in creating source-to-target mappings and functional specifications for data pipelines

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• Strong SQL skills for data analysis, including joins, aggregations, window functions, and data validation queries.

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• Experience working with modern data platforms such as Snowflake, Databricks, or similar cloud-based ecosystems.

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• Familiarity with data warehousing concepts, dimensional modeling, and data lake architectures

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• Strong analytical thinking and ability to interpret complex datasets and business rules.

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• Experience working in Agile delivery environments.

Preferred Qualifications

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• Exposure to tools/platforms commonly used in investment data ecosystems (e.g., Bloomberg, FactSet, Aladdin, Burgiss, or similar).

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• Understanding of data governance frameworks, including data quality, lineage, and stewardship.

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• Experience with ETL/ELT tools or orchestration frameworks (e.g., Airflow).

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• Basic understanding of Python/PySpark for data analysis is a plus.

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• Prior experience in working with consulting firms or investment advisors is highly desirable.

Key Competencies

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• Strong communication skills with the ability to interact with both business and technical teams.

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• Attention to detail, especially in data mapping and validation activities.

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• Problem-solving mindset with the ability to identify data issues and propose solutions.

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• Ability to manage multiple priorities in a fast-paced transformation environment.