Senior Technical Lead (170174)

Job Summary

Key Responsibilities

• Design and build reusable AI skills, prompts, agents, and instruction files for dbt and data engineering workflows.
• Develop AI capabilities for Jira story intake, impact analysis, technical design, dbt model generation, testing, and code review.
• Build automation for CTM configuration validation, dependency sequencing, scheduling alignment, and deployment-readiness checks.
• Develop deployment skills covering GitLab merge requests, CI/CD pipelines, dbt Cloud execution, release runbooks, and change evidence.
• Build automated regression-testing and data-reconciliation capabilities across development, pre-production, and production environments.
• Apply strong hands-on knowledge of dbt models, macros, materializations, incremental strategies, tests, documentation, lineage, and dbt Fusion.
• Use Snowflake metadata, dbt manifests, GitLab repositories, and lineage information to identify upstream and downstream change impacts.
• Develop Python-based automation for API integration, metadata processing, validation, structured outputs, and workflow orchestration.
• Create reusable engineering standards for SQL, dbt, testing, data modeling, error handling, observability, and repository structure.
• Build AI-assisted support for pipeline monitoring, data freshness, anomaly analysis, defect investigation, and production reconciliation.
• Integrate AI-assisted workflows with GitHub Copilot, Jira, Confluence, GitLab, Snowflake, dbt Cloud, CTM, and approved MCP servers.
• Create golden datasets and evaluation scenarios to measure AI-draft acceptance, accuracy, rework, test coverage, and edge-case handling.
• Review AI-generated artifacts for business-logic accuracy, maintainability, security, performance, and compliance with project standards.
• Support pilot implementation, developer enablement, troubleshooting, and scaled adoption across the dbt project estate.
• Collaborate with developers, technical leads, architects, QA teams, platform teams, and deployment stakeholders throughout the lifecycle.

Skill Requirements

• Skill set: DBT, Snowflake, Python, and AI
• USAA experience is mandatory

Other Requirements

• The selected resources will contribute to AI-driven engineering solutions covering requirements analysis, impact assessment, development, automated testing, deployment orchestration, reconciliation, and production support.