Job summary
Experience: 10 +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.