AI Data Engineer

Requirements:

• Strong skills in dbt, Snowflake, Python, and AI.
• Hands-on expertise with dbt models, macros, materializations, incremental strategies, tests, documentation, lineage, and dbt Fusion.
• Ability to use Snowflake metadata, dbt manifests, GitLab repositories, and lineage information to assess upstream and downstream impacts.
• Experience developing Python automation for API integrations, metadata processing, validation, structured outputs, and workflow orchestration.

Responsibilities:

• Design reusable AI skills, prompts, agents, and instruction files for dbt and data engineering workflows.
• Develop AI support for Jira story intake, impact analysis, technical design, dbt model generation, testing, and code review.
• Automate CTM configuration validation, dependency sequencing, scheduling alignment, and deployment-readiness checks.
• Create deployment capabilities for GitLab merge requests, CI/CD pipelines, dbt Cloud execution, release runbooks, and change evidence.
• Build automated regression testing and data reconciliation across development, pre-production, and production environments.
• Establish reusable standards for SQL, dbt, testing, data modeling, error handling, observability, and repository structure.
• Develop 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 assess AI-draft acceptance, accuracy, rework, test coverage, and edge-case handling.
• Review AI-generated work for business-logic accuracy, maintainability, security, performance, and compliance with project standards.
• Support pilot implementation, developer enablement, troubleshooting, and broader adoption across the dbt project portfolio.
• Collaborate with developers, technical leads, architects, QA and platform teams, and deployment stakeholders throughout the project lifecycle.

Technologies:

• AI
• API
• CI/CD
• Cloud
• Copilot
• Confluence
• GitHub
• GitLab
• Support
• JIRA
• Marketing
• MCP
• Python
• SQL
• Security
• Snowflake
• dbt

More

We offer a strategic opportunity within EDAO to build and implement AI-assisted engineering capabilities across 31 production dbt projects in the Marketing Analytics portfolio. The initiative connects GitHub Copilot with dbt, Snowflake, GitLab, Jira, Confluence, dbt Cloud, and CTM workflows, with governance and human oversight. The pay range is $50–$55 per hour. Our benefits include medical, dental, and vision insurance; a 401(k); HSA; short- and long-term disability and life and AD&D insurance; paid sick leave where required by law; supplemental insurance; identity theft protection; pet insurance; wellness programs; an employee assistance program; and career development opportunities. Eligibility and terms may vary by employment status, tenure, and location, and plans may change in accordance with applicable law. Founded in 2010 and headquartered in the Washington, DC metro area, Cynet Systems Inc. provides technology staffing and workforce solutions to Fortune 500 companies, government agencies, and enterprises across the United States and Canada. We serve IT, engineering, life sciences, clinical, and professional staffing needs through recruiting operations in North America and Asia. We are a certified Minority Business Enterprise and hold ISO 9001, ISO 14001, ISO 27001, and SOC 2 Type II certifications.

last updated 43 week of 2026