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Manager of Data & Analytics

Job in San Diego, San Diego County, California, 92189, USA
Listing for: Mission Wealth
Full Time position
Listed on 2026-01-26
Job specializations:
  • IT/Tech
    Data Analyst, Data Engineer, Business Systems/ Tech Analyst, Data Science Manager
Job Description & How to Apply Below

Overview

As a Barron’s Top 100 RIA firm and voted Best Places to Work by Fortune, Mission Wealth is hiring a growth-minded Manager of Data & Analytics to join our award-winning team! If you are ready to elevate your career in a leading wealth management company with a commitment to giving back to the community and expanding nationally, let’s go!

As a Manager, Data & Analytics
, you would help scale our data platform, strengthen analytics foundations, and deliver production-grade data solutions that enhance advisor productivity, client experiences, and business decision-making. You will serve as a hands-on technical leader and strategic partner to the Director of Data & Analytics, supporting the daily execution and continued professionalization of Mission Wealth’s data ecosystem.

You will collaborate closely with Technology, Operations, M&A, Finance, and Advisor teams to understand business needs, design scalable data solutions, and deliver analytics that drive efficiency, accuracy, and insight across the firm. This role requires a mix of data engineering, analytics development, systems thinking, and cross-functional communication.

You’ll be instrumental in building and operating a reliable, governed data platform while helping the organization move toward more automated, standardized, and insight-driven workflows using modern data best practices. Mission Wealth has offered 360-degree wealth management services to affluent families since 2000. Our dynamic planning process ensures that every piece of the puzzle is put into place as our clients’ lives unfold and their needs evolve.

This gives them the complete picture and confidence in their financial future.

Day-to-Day as a Manager, Data & Analytics

Data Platform and Engineering

  • Design, build, and operate scalable data pipelines and datasets to support analytics and reporting across the firm
  • Develop and maintain Python-based ETL workflows, batch processing jobs, and orchestration schedules
  • Support the implementation and ongoing operation of a modern cloud data warehouse (Snowflake preferred)
  • Integrate data from core systems including Salesforce (Financial Services Cloud), Tamarac, custodians, and financial planning platforms
  • Partner on M&A onboarding efforts by supporting repeatable data ingestion, validation, and integration processes

Analytics & Reporting

  • Build and maintain analytics-ready data models using SQL and versioned datasets
  • Deliver dashboards and reports that provide actionable insights for advisors, operators, and leadership
  • Support BI tools such as Power BI, Tableau, or similar platforms used across the organization
  • Ensure analytics outputs are accurate, well-documented, and aligned with business definitions

Data Governance & Quality

  • Maintain high data quality standards through validation checks, monitoring, and issue resolution
  • Partner with Compliance and Technology teams to support data security, PII handling, and retention practices
  • Help establish foundational data governance practices, including lineage awareness and documentation
  • Reduce single points of failure by institutionalizing processes, runbooks, and SOPs

AI & Automation

  • Partner with business and technology stakeholders to identify high-impact advisor and operations workflows that can be automated using data-driven triggers, rules, and orchestration (e.g., client onboarding, service requests, referral follow-ups, and M&A data intake).
  • Build “AI-ready” datasets (clean, labeled, governed, and versioned) that enable scalable use cases like intelligent routing, next-best-action recommendations, and proactive client/advisor insights.
  • Develop and operationalize automated data-quality monitoring (anomaly detection, reconciliations, completeness checks) with alerting and clear remediation paths to reduce manual oversight and rework.
  • Support experimentation and deployment of practical AI capabilities—such as natural-language search over firm data, automated narrative summaries for dashboards, and guided insights for advisors—while ensuring appropriate controls for PII and compliance.
  • Implement workflow automation patterns that connect core systems (Salesforce, Tamarac, custodians, planning tools) to…
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