Job Description
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Company Overview
A leading private wealth management firm based in San Francisco manages more than $21.1 billion in aggregate assets under management for more than 500 families. The organization is focused on putting clients’ interests first and delivering thoughtful, long-term wealth management solutions.
Primary Responsibilities
IBOR / Reporting Transition & Integration
- Lead the design, implementation, and migration of the firm’s data architecture supporting the new IBOR/Reporting environment.
- Define and maintain core data models and entity mappings connecting reporting, CRM, operational, and investment systems.
- Design integration patterns and transformation logic that align data definitions across Practifi and other internal and external systems.
- Partner with Operations, Client Service, and business stakeholders to ensure reporting systems meet requirements for timeliness, accuracy, auditability, and downstream usability.
- Establish monitoring, quality checks, reconciliation processes, and exception-handling procedures to support reliable production reporting.
- Help manage the transition from legacy data flows to modernized data environments.
Data Lake, Internal Data Normalization & Governance
- Own the design and supervise implementation of the firm’s long-term data lake environment and related governance processes.
- Organize investment, client, operational, and knowledge data into a coherent, normalized, and well-documented ecosystem.
- Design and manage centralized data models, identifiers, hierarchies, and classifications to support consistent data reconciliation and reuse.
- Implement data quality frameworks, lineage standards, access controls, and documentation practices.
- Create reusable and governed data products and interfaces supporting reporting, analysis, oversight, and information reuse.
- Work with internal stakeholders to improve data completeness, latency, usability, scalability, and maintainability.
AI-Ready Data Environment, Firm Knowledge & Skills Enablement
- Create data structures, metadata, and access patterns that enable AI tools to reliably query and deliver high-quality information.
- Structure structured and unstructured firm information so recurring inquiries can be answered using trusted data and governed business logic.
- Collaborate with business process specialists and subject matter experts to define and build Skills that route recurring questions to appropriate data sources, business rules, and presentation formats.
- Design and maintain query-ready data models and semantic context that improve the relevance, consistency, and explainability of information delivered through LLM-based tools.
- Prioritize data engineering initiatives that improve retrieval quality, response accuracy, and presentation capabilities for internal knowledge and decision-support use cases.
- Support repeatable inquiry patterns, presentation frameworks, and knowledge artifacts grounded in current and reliable firm data
Required Qualifications
- 5–10 years of relevant experience in data engineering, data platform development, data pipeline development, or related roles.
- Experience in financial services, fintech, wealth management, investment management, or adjacent industries is preferred.
- Direct experience architecting and maintaining production data environments supporting reporting, analytics, operational workflows, or enterprise information access.
- Experience aligning data models across multiple business systems.
- Experience translating business requirements into durable data integration logic.
- Strong understanding of data quality, lineage, governance, and auditability.
- Experience designing data environments that support search, semantic retrieval, AI-enabled querying, or knowledge systems is a plus.
- Exposure to investment, wealth management, or financial data is strongly preferred.
- Strong communication and collaboration skills with the ability to work effectively with technical and non-technical stakeholders.
- Ability to develop scalable, maintainable, and well-documented data solutions.
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