Vice President, Senior Data Analyst - SMA Solutions

BlackRock•San Francisco, CA

6d•$147,500 - $195,000•Hybrid

About The Position

The Senior SMA Data Analyst is responsible for ensuring the integrity, accuracy, and operational reliability of client and account data across Salesforce and Entity Master platforms supporting SMA Solutions. This role sits at the intersection of business operations and technology, requiring a combination of hands-on data analysis, technical proficiency, and strong business judgment. The data analyst will play a critical role in resolving daily data discrepancies that impact account onboarding, servicing, and client workflows, while contributing to long-term data quality and automation initiatives. The need for this role is driven by a continuous volume of data reconciliation issues that require dedicated ownership to maintain day-to-day business continuity. The successful candidate will combine strong analytical and technical skills with business context to support account onboarding, client servicing, operational workflows, and strategic data quality initiatives across SMA Solutions.

Requirements

Bachelor's degree or equivalent experience in Data Analytics, Information Systems, Computer Science, Finance, or a related field
Strong proficiency in SQL, SOQL, Excel, and data analysis techniques
Experience working with Salesforce or similar CRM and enterprise data platforms
Familiarity with Snowflake, Power BI, Python, or similar analytical and reporting tools
Strong understanding of data governance, data quality, and reconciliation processes
Deep familiarity with relational data models, master data concepts, and complex entity relationships
Ability to investigate data issues, perform root cause analysis, and implement scalable solutions
Strong analytical, problem-solving, communication, and stakeholder management skills

Nice To Haves

Experience within the financial services, wealth management, asset management, banking, or brokerage industry
Understanding of advisor, client, account, and corporate hierarchy structures, including intermediary and end-investor relationships
Experience supporting client data, master data, data quality, or reference data management functions
Experience designing or validating automated reconciliation processes and data quality controls

Responsibilities

Perform manual reconciliation of data discrepancies between CRM and Master Data Management across various client defining objects
Resolve data breaks that impact operational workflows, including onboarding blockers and sync failures
Support the development of automated reconciliation capabilities as part of the broader data quality roadmap
Investigate recurring data issues, including: Record merges originating from Data Operations Team, Duplicate records and conflicting attributes across systems, Missing or incomplete MDM records, Operationally significant contact conflicts
Conduct root cause analysis and recommend scalable, systemic solutions
Track and monitor ongoing data reconciliation issues and patterns
Develop reporting to quantify issue volume, trends, and business impact
Escalate high-frequency or systemic issues to Salesforce Engineering, Data Engineering, or Data Operations teams for resolution
Utilize SQL, SOQL , and Excel to query, analyze, and remediate data across Salesforce and MDM datasets
Perform validation and reconciliation across multiple data sources, including Snowflake where applicable
Develop a strong understanding of business processes, including: Account onboarding and servicing workflows, Client hierarchy and relationship models, Operationally significant records and dependencies
Apply business context to inform reconciliation decisions and prioritization
Maintain clear documentation of reconciliation processes, issue types, and resolution steps
Build process guides, playbooks, and onboarding materials
Identify opportunities to streamline workflows and reduce manual effort
Partner cross-functionally across business, data operations, and IT Engineering teams
Act as a bridge between business users and technical teams to drive resolution of data issues