Agentic AI Data Engineer - Face to Face Interview

Agentic AI Data Engineer

Baltimore, MD (Hybrid)

12+ Months Contract

Job Description:

Required Skills and Experience:

• 10+ years of IT experience in data engineering, analytics, and enterprise data systems.
• Strong hands-on experience with Snowflake, Python, advanced SQL, and ETL pipeline development.
• Strong knowledge of AI agents, AI-driven automation, and integrating AI capabilities into data engineering workflows.
• Experience building AI-powered tools, accelerators, and solutions to improve data analysis, automation, and engineering productivity.
• Experience with legacy system modernization, reverse engineering, and forward development, with a focus on leveraging AI to analyze legacy code and data pipelines.
• Strong understanding of AWS services, including Lambda, Step Functions, and ECS.
• Experience with Airflow, Unix shell scripting, and data warehouse concepts.
• Knowledge of dimensional data modeling and modern enterprise data architecture.
• Experience with dbt is a plus.
• Experience with Slingshot and building tools and accelerators for data analysis.
• Experience building and maintaining enterprise-wide data and analytics systems.
• Experience in financial services, asset management, or financial markets is preferred.

Roles and Responsibilities:

• Design, develop, and maintain scalable Snowflake data pipelines using Python and advanced SQL.
• Develop and implement AI agent-based solutions to automate data engineering tasks, accelerate analysis, and improve workflow efficiency.
• Leverage AI tools and techniques for legacy code analysis, reverse engineering, documentation, and data pipeline modernization.
• Build AI-powered tools and accelerators to support enterprise data analysis, code transformation, and modernization initiatives.
• Modernize legacy applications, codebases, and data pipelines through reverse engineering and forward development.
• Build and optimize ETL workflows, dimensional models, and data warehouse solutions.
• Integrate AWS services to support data processing, orchestration, and automation.
• Collaborate with business and technical teams to deliver scalable, AI-enabled enterprise data and analytics solutions.