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Agentic AI Data Engineer - Face to Face Interview

Full-time

Centraprise

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.
Vacancy posted 2 hours ago
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