Data Analyst

Senior Data Analyst Wealth Management Practice | Data Engineering & AnalyticsDOMAINWealth Management TECHNICAL COREAdvanced SQL / STTMCLOUD ENVMS Azure (Preferred)
EXPERIENCE5+ Years Senior Level Key Objective:
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.

Role Overview As a Senior Data Analyst in our Wealth Management technology practice, you will play a central role in shapingclient and portfolio data solutions. You will be responsible for navigating complex legacy and modern data structures—including client profiles, accounts, holdings, transactions, performance metrics, and advisory billingdata.

You will perform deep-dive data profiling and pattern analysis using advanced SQL, assess data health and quality,and author comprehensive Source-to-Target Mapping (STTM) documentation. Crucially, you will act as the principal functional contact for ETL/Data Engineers, effectively translating business logic into actionableengineering specifications and facilitating clear walkthroughs.

• Data Profiling & Pattern Analysis:
  Execute complex SQL queries across relational databases, data lakes, andwarehouses to analyze data distribution, evaluate data quality, discover data anomalies, and identify underlyingrelational patterns.
• Source-to-Target Mapping (STTM):
  Design, author, and maintain robust, granular STTM documents detailingbusiness rules, field transformations, data types, primary/foreign key relationships, and data pipeline logic.
• Developer Collaboration & Bridge:
  Conduct detailed walkthroughs of mapping documents with engineering teams (ETL/Data Pipeline developers), clarifying edge cases, data constraints, and business intent to drivesmooth implementation.
• Data Quality & Governance:
  Establish baseline data quality metrics, define data validation rules, and collaborate with data governance leads to remediate data discrepancies or gaps across financial datasets.
• Wealth Management Domain Application:
  Analyze domain-specific data entities, including householdrelationships, investment portfolios, asset classes, custody positions, fee calculations, and trade histories.
• Stakeholder Communication:
  Articulate data insights, structural risks, and mapping dependencies clearly toboth technical developers and non-technical business stakeholders/product owners.
• Testing & Acceptance Support:
  Assist QA and engineering teams during sprint cycles by validatingtransformed datasets against original target specifications using customized SQL validation scripts.

Confidential
- Wealth Management Practice Page 1 of 2

• Experience:
  
  5+ years of hands-on experience as a Data Analyst, Data Modeler, or Technical Business Analystin enterprise data environment initiatives.
• Advanced SQL Expertise:
  Proven mastery in writing complex SQL scripts (multi-table JOINs, CTEs, windowfunctions, 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, structuralinconsistencies, 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.