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
Job source
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 (AWSβs 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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