Data Architect

RFG Advisory•Dallas, TX

13h•Hybrid

About The Position

RFG Advisory is seeking a hands-on data leader to own its Snowflake-based data platform end to end. The platform consolidates information from business systems to support dashboards, search, and AI assistants used by the firm and its clients. The role is responsible for making data accurate, secure, governed, and ready for AI. It is a player-coach position combining senior technical ownership and hands-on production work with setting standards for a growing team. The first year is expected to be primarily focused on building. The role may be based in the Birmingham office or remotely. Birmingham employees follow a hybrid schedule of three days in the office and two remote; remote employees are expected to travel to Birmingham occasionally, including for onboarding. The position reports to the VP of Technology. The Data Architect will own Snowflake architecture and operations, reliable data pipelines, data modeling and metric governance, client data protection, AI-ready semantic access, migrations, reporting, and partner engineering standards. The role also defines the data architecture roadmap, establishes data quality and release practices, and supports leadership reporting using governed metrics. RFG Advisory describes itself as a growth platform for independent financial advisors and emphasizes innovation, collaboration, execution, servant leadership, and continuous improvement. The hiring process may use automated tools to assist with resume review, while qualified human reviewers make hiring decisions. RFG Advisory is an equal opportunity employer and provides reasonable accommodations during the application and hiring process.

Requirements

At least 8 years of experience in data engineering or data architecture, including at least 2 years as technical lead for a data platform, team, or major data initiative.
A track record of balancing hands-on delivery with leading the work.
Deep, hands-on Snowflake experience, including data modeling, tasks and dynamic tables, role-based access control, row access and masking policies, and cost management.
Expert SQL and dimensional modeling skills.
Working Python skills for pipelines and automation.
Experience with dbt or a similar transformation framework, Git, and CI/CD.
Experience designing row-level data access so customers, offices, or business units see only their own data.
Ability to turn business requirements into technical designs and specifications and explain data trade-offs clearly to executives, business users, and engineers in writing, conversation, and diagrams.
Proactive approach to challenging the status quo and asking probing questions to improve how data is managed and used.
Ability to stay hands-on while setting standards and raising the capability of others.
Has managed people or is ready to grow into managing a small data team.
Bachelor's degree in Computer Science, Information Systems, or a related field, or equivalent professional experience.

Nice To Haves

Financial services data experience; wealth or asset management experience is a plus.
Experience with semantic layers and AI data access, such as Snowflake Cortex or semantic views.
Experience integrating CRM data, especially Salesforce, with a data warehouse.
Experience working with outsourced or vendor development teams.
Familiarity with SEC and FINRA expectations for protecting client data.
Relevant certifications such as SnowPro Advanced (Architect or Data Engineer), CDMP, or a cloud data credential for Azure, AWS, or GCP.
Proficiency with AI tools such as Claude, ChatGPT, or Microsoft Copilot to improve productivity, pipeline design, and data analysis workflows.
A master's degree.

Responsibilities

Own the Snowflake environment, including account structure, environments, compute, performance, and cost.
Run reliable pipelines from core financial, CRM, marketing, and other business systems, with monitoring for freshness, completeness, and errors.
Put data logic under version control and establish 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 data impact and produce high-level designs before work begins.
Simplify the data landscape by removing duplicate data and pipelines and maintaining current diagrams of data flows.
Design and deliver a canonical data model for 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 through a data catalog with business definitions and lineage, data quality rules and monitoring, and named owners for key data.
Design, maintain, and regularly test row-level access so users and business units only see entitled data across data surfaces.
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 to keep data practices current.
Build a documented semantic layer that AI assistants and internal tools can query safely.
Provide AI and engineering teams with governed datasets and access patterns so new tools can ship quickly.
Lead data work for system migrations.
Deliver the firm scorecard and leadership reporting using governed metrics shared across the firm.
Hold technology vendors and development partners to clear data standards and maintain the firm's ability to move data and logic between platforms.
Guide and upskill vendor engineers by setting quality standards, reviewing their work, and managing technical dependencies and roadmap milestones across teams.

Benefits

Competitive salary and bonus pool.
Generous paid time off, holidays, and a Charitable Service Day.
Health, dental, and vision insurance, plus an RFG Advisory stipend.
Flexible Spending Account for health and dependent care, plus HSA for applicable coverage.
Lifestyle Spending Account.
401(k) with Safe Harbor contribution.
Paid parental leave.
Short- and long-term disability insurance.
Life insurance.
Surface Pro and home office setup.
Pet insurance.
Continuing education and professional development support.