AI Data Engineer (Logical DBA Focus)
Location: Austin, TX (Onsite Local Candidates Only)
Duration: 6 Months Contract-to-Hire
Positions: 1
Important Requirement
Candidates MUST currently reside within 50 miles of Austin, TX (500 W 2nd Street, Suite 1500, Austin, TX 78701) before the start date.
Job Overview
We are seeking an experienced AI Data Engineer with a strong Logical Database Administration (DBA) background to support enterprise AI initiatives. This role is heavily focused on database administration, data architecture, PL/SQL development, and AI-ready data platforms rather than DevOps or infrastructure engineering.
The ideal candidate will have extensive experience administering Oracle, PostgreSQL, MySQL, and MongoDB Atlas databases while designing scalable data architectures that support Artificial Intelligence and Machine Learning initiatives.
Required Skills
Advanced experience with Oracle PL/SQL and SQL
Strong Logical Database Administration experience
Database schema design, DDL, DML, stored procedures, functions, triggers, and performance tuning
Experience with Oracle, PostgreSQL, MySQL, and MongoDB Atlas
Experience with GitHub version control and CI/CD workflows
AI & Data Testing experience
Shell scripting for database automation and maintenance
Strong analytical and troubleshooting skills
Preferred Skills
AWS database technologies (RDS, EC2, S3)
Experience administering multi-platform database environments
AI/ML data pipeline experience
Data architecture and enterprise data modeling
Backup & Recovery strategies
Database monitoring and optimization
Key Responsibilities
Design, develop, and maintain scalable enterprise data architectures supporting AI initiatives.
Perform Logical DBA activities including schema design, DDL/DML development, stored procedures, database optimization, performance tuning, indexing, and data integrity.
Administer Oracle, PostgreSQL, MySQL, and MongoDB Atlas databases across AWS environments.
Develop and optimize Oracle PL/SQL packages, procedures, functions, and SQL queries.
Build and maintain AI-ready data pipelines supporting enterprise analytics and machine
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