Senior Data Analyst | Wealth Management Practice

Introduction

We are seeking a highly analytical Senior Data Analyst to lead data discovery, quality profiling, and Source-to-Target Mapping (STTM) for enterprise wealth management data platforms. This role serves as the critical bridge between wealth business teams and engineering developers.

Responsibilities

• Data Profiling & Pattern Analysis
• Source-to-Target Mapping (STTM)
• Developer Collaboration & Bridge
• Data Quality & Governance
• Wealth Management Domain Application
• Stakeholder Communication
• Testing & Acceptance Support

Requirements

Minimum Qualifications

• Experience: 5+ years of hands-on experience as a Data Analyst, Data Modeler, or Technical Business Analyst in enterprise data environment initiatives.
• Advanced SQL Expertise: Proven mastery in writing complex SQL scripts (multi-table JOINs, CTEs, window functions, subqueries, and analytical functions) for data extraction and profiling.
• STTM Documentation: Demonstrated experience creating explicit, comprehensive Source-to-Target Mappings (STTM) for ETL/ELT pipelines, reporting, or data warehouse migrations.
• Data Quality & Profiling: Strong background in identifying data anomalies, missingness, structural inconsistencies, and data integrity issues.
• Communication Skills: Exceptional verbal and written communication skills with proven experience leading technical specification reviews with software developers and architects.
• Education: Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Finance, or a related quantitative field.

Preferred Experience & Skills

• Wealth Management Domain Knowledge: Direct experience working with financial, wealth, investment management, brokerage, or banking data domains (e.g., portfolio management, custodial feeds, advisory accounts).
• MS Azure Cloud Environment: Exposure to or experience working with cloud data platforms on Microsoft Azure (e.g., Azure Synapse Analytics, Azure Data Factory, Azure Data Lake Storage, or Databricks on Azure).
• Modern Data Stacks: Familiarity with modern data modeling concepts (Dimensional, Snowflake, Data Vault) and orchestration workflows.
• Agile/Scrum Framework: Experience working in Agile/Scrum delivery models, managing user stories, and utilizing tools like Jira or Azure DevOps.

Core Skills & Competencies

• Advanced SQL
• Source-to-Target Mapping (STTM)
• Data Profiling & Quality
• Developer Communication
• Wealth Management Domain
• MS Azure Cloud
• Data Pipeline Specification
• Relational Modeling
• Jira / Azure DevOps
• Data Lineage