Data Engineer

The Data Engineer is a hands-on technical role focused on full-stack data engineering within the Enterprise Data organization. The role will play a critical part in shaping future big data, analytics, and AI agent engineering initiatives using Snowflake, DBT, SQLDBM, and Medallion architecture.

Bachelor s degree in computer science, Computer Information Systems, Engineering, Statistics or closely related field (willing to accept foreign education equivalent) (required). Experience in AWS services for data and analytics (required). 5 years of experience in Data Ingestion, Data Extraction, and Data Integration (required). Hands-on experience with Snowflake, DBT, advanced SQL, SQLDBM, and Medallion architecture (required). Experience designing or integrating AI agents within data engineering or analytics solutions (required)., 5+ years of experience in Enterprise Information Solution Architecture, Design, and development required. 5+ years of experience with integration architectures such as SOA, Microservices, ETL or other integration technologies. 5+ years of experience with working content or knowledge management systems, search engines, relational databases, NoSQL databases, ETL tools, geospatial systems, or semantic technology. 5+ years of hands-on experience with AWS services ( S3, Kinesis, Lambda, Athena, Glue, EMR) required. Experience with JSON or XML data modeling required. Experience with Git/GitHub, branching, and other modern source code management methodologies required. Domain knowledge of NoSQL or relational database required. Understanding of database architecture and performance implications required. Experience integrating Business Intelligence applications like PowerBI. Experience with Machine Learning and Artificial Intelligence. Ability to multi-task effectively. Ability to work collaboratively as part of an Agile Team. Extensive knowledge and experience with Python and Snowflake Streamlit. Excellent written and verbal communication skills, sense of ownership, urgency and drive. Experience building governed AI agent solutions using enterprise data, semantic models, vector search, or retrieval-augmented generation patterns. Experience establishing DBT development standards, automated data tests, documentation, lineage, and production deployment controls. Experience designing enterprise data models and warehouse schemas in SQLDBM for Snowflake-based platforms.