Data Engineer, AI & Automation

Description

Location &

Hours:

Fort Lauderdale HQ | On-site, Full-time

Department: Sound Income Strategies

FLSA Classification: Exempt

Sound Income Strategies, a Sound Income Group company, is a Registered Investment Adviser (RIA) with $4.5 billion in assets under management. The firm provides discretionary and non-discretionary investment management services to independent financial advisors and their clients nationwide. As a fiduciary, Sound Income Strategies is committed to portfolio oversight, regulatory compliance, and disciplined investment implementation aligned with clients’ objectives.

Sound Income Strategies is seeking a Data Engineer, AI & Automation to modernize our operational data infrastructure, reporting, and business workflows. Reporting directly to the Chief Technology Officer, this hands-on individual contributor will serve as the primary internal owner of backend data engineering and applied AI automation.

This role combines Snowflake expertise, strong data analysis, and production software engineering to consolidate information from custodians, trading platforms, portfolio reporting systems, and other business sources. The ideal candidate can understand how our teams work, identify valuable improvements, and independently build, deploy, and maintain reliable tools that employees use in their daily work.

Data Engineering and Data Quality

• Develop and maintain backend data pipelines, integrations, and data models in Snowflake to support accurate, accessible operational data.
• Learn and work within the existing data aggregation architecture; integrate and reconcile information from custodians such as Schwab, trading platforms such as Orion, portfolio reporting systems such as Black Diamond, and supplemental sources.
• Analyze source data, investigate discrepancies, and implement validation, reconciliation, and quality checks to ensure reporting and downstream applications use complete, accurate information.
• Translate complex data into useful business outputs and partner with internal stakeholders and front-end contributors to validate dashboards, reports, and application functionality.

Applied AI and Workflow Automation

• Meet directly with Operations and other SIS teams to understand manual processes, define requirements, and prioritize improvements with the CTO.
• Build and deploy backend services, internal tools, and automations that improve operational efficiency and reduce repetitive manual work.
• Develop production AI functionality using Anthropic Claude, including document retrieval, text extraction, document understanding, and multi-step workflows.
• Implement and maintain Model Context Protocol (MCP) integrations connecting AI applications to approved tools and data sources, with appropriate permissions and human review.
• Use managed model platforms such as Snowflake Cortex, Amazon Bedrock, Google Vertex AI, or comparable services to support practical business applications.

Production Ownership and Collaboration

• Own solutions from requirements and design through testing, deployment, documentation, user adoption, and ongoing support.
• Monitor data pipelines and AI workflows; troubleshoot failures, evaluate output accuracy, and improve reliability, performance, and operating costs.
• Implement access controls, logging, and appropriate safeguards for sensitive client and financial data in collaboration with the CTO and Compliance.
• Participate in vendor and platform implementation meetings, learn existing systems, and coordinate technical dependencies across internal teams and external partners.
• Maintain clear technical documentation and user guidance, and communicate priorities, progress, risks, and results to…