Help Build the IRA of the Future

RFG Advisory supports independent financial Advisors with the technology, investment, and operational resources they need to grow their practices. We are scaling quickly, and technology, data, and AI are central to how we serve Advisors and their clients.

We are looking for a hands-on data leader to own our data platform end to end. Our platform runs on Snowflake and brings together data from many business systems to power dashboards, search, and AI assistants used across the firm and by our clients. You will make that data accurate, secure, well-governed, and ready for AI. This is a player-coach role: you will be our senior data expert and will personally write production SQL, design data models, and make the call on data questions, while setting the standards a growing team will follow. Expect to spend most of your first year building.

Location: This role can be in our Birmingham office or remote.

• If in Birmingham, AL, our office works a hybrid schedule (3 days in-office, 2 remote). 
• If remote, occasional travel to Birmingham will be required including onboarding.

Reports to: VP of Technology



What You'll Do

Data Platform Ownership

• Own our Snowflake environment: account structure, environments, compute, performance, and cost.
• Run reliable pipelines from core business systems, including financial, CRM, and marketing platforms, with monitoring for freshness, completeness, and errors.
• Put all data logic under version control with code review, automated testing, and a defined release process.
• Define the target data architecture and roadmap, including reference architecture and standard integration patterns.
• Tune performance, troubleshoot issues, and own backup, recovery, and retention for data assets.
• Review new projects and requests for their data impact and produce high-level designs before work starts.
• Simplify the data landscape: remove duplicate data and pipelines, and keep current diagrams of how data flows across systems.

Building the Data Model & Metric Layer

• Design and deliver a canonical data model for the firm's core business entities such as clients, accounts, and transactions.
• Create a governed catalog of business metrics with clear definitions, owners, and tests.
• Reconcile key figures to source systems and the general ledger, and publish the results.
• Establish data governance: a data catalog with business definitions and lineage, data quality rules and monitoring, and named owners for key data.

Client Data Protection

• Design and maintain row-level access so each user and business unit sees only the data they are entitled to across every data surface, and test it regularly.
• Lead classification, masking, and access reviews for client personal information in partnership with IT and Security.
• Track changing privacy and data protection rules and partner with Compliance so our data practices stay ahead of them.

AI Readiness

• Build a documented semantic layer that AI assistants and internal tools can query safely.
• Give AI and engineering teams governed datasets and access patterns so new tools can ship quickly.

Migrations, Reporting & Partner Management

• Lead the data work for system migrations.
• Deliver the firm scorecard and leadership reporting on the same governed metrics used across the firm.
• Hold technology vendors and development partners to clear data standards, and keep the firm able to move its data and logic between platforms.
• Guide and upskill vendor engineers: set quality standards, review their work, and manage technical dependencies and roadmap milestones across teams.