W2: Developer Specialist/Database Modernization Engineer McLean, VA(Onsite)

Stellent IT LLC
McLean, VA, United States
18 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Starter
Experience required
1 year minimum
Working hours
Regular working hours

Tech stack

Legacy Database Java (Programming Language) SAP Sybase Adaptive Server Enterprise Artificial Intelligence Amazon Web Services Databases Data Architecture Information Engineering Python (Programming Language) PostgreSQL Operational Data Store Data Streaming
+7 more
Scripting Snowflake Database Migration Apache Kafka Front End Software Development Code Restructuring Data Pipelines

Job description

Primary Objective: Modernize a legacy Operational Data Store (ODS) by converting legacy database schemas, refactoring data pipelines, and implementing AI-driven automation to build solutions from scratch. This is primarily a Database Modernization / Data Engineering position rather than a traditional Full-Stack role. The target environment involves transitioning from a legacy Sybase database to a modern cloud/relational architecture (PostgreSQL or Snowflake) using AI tools like Amazon Kiro. Key Responsibilities & Outcomes

  • Convert legacy database schemas and refactor data pipelines.
  • Implement AI-driven automation to build components from scratch.
  • Utilize Amazon Kiro (AWS’s agentic AI IDE/environment) to automate code refactoring, spec generation, and schema conversions.
  • Focus entirely on back-end data architecture and database migration (minimal to no frontend work).

Requirements

  • 1-3 years of AI experience.
  • 8 years of development experience.
  • Deep database transformation and data engineering experience.
  • Strong underlying database/data engineering capabilities (ability to learn Amazon Kiro on the job is acceptable if these core skills are strong).

Preferred:

  • Prior hands-on experience with AI-assisted development or agentic tools.
  • Experience with Java/Python (used primarily for scripting, data pipelines, or basic glue logic).
  • Experience with Kafka (beneficial for understanding real-time streaming contexts).

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