AI-Enabled Data Engineer

Data Engineer AI & Data Solutions We are seeking a Data Engineer to join a software development team focused on building and delivering scalable AI-enabled applications. This role involves developing production-ready solutions that integrate modern AI technologies into enterprise systems. The ideal candidate can contribute quickly in a collaborative environment and work closely with technical and business stakeholders to deliver reliable, high-quality solutions. This is a full-time onsite opportunity located near Columbus, Ohio. Responsibilities Design and maintain data models, database structures, and storage solutions Develop and support ETL/ELT pipelines for ingesting and transforming data Monitor and improve database and pipeline performance Ensure data quality, consistency, and integrity across systems Assist with SQL development and troubleshooting Contribute to data warehouse and data lake initiatives Collaborate with engineering and cross-functional teams to meet project goals Follow established development standards, documentation practices, and operational procedures Complete assignments independently with accuracy and professionalism Qualifications Bachelor s degree in Computer Science, Software Engineering, Computer Engineering, or related experience Around 1 3 years of experience in software or data engineering Strong Python programming skills with experience writing maintainable production code Experience integrating AI services, APIs, or machine learning tools into applications Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform Experience with data warehousing and analytics platforms such as Databricks or Redshift Knowledge of cloud storage solutions including S3 or Azure Storage Experience with ETL/orchestration tools like Airflow, Glue, ADF, or NiFi Ability to work within established coding standards and system architectures Strong communication and collaboration skills Preferred Skills Exposure to AWS services such as Lambda, EC2, S3, or Bedrock Familiarity with Docker, CI/CD pipelines, MLOps, or enterprise-scale data environments Understanding of responsible AI or governance practices is a plus Work Environment Full-time schedule (40 hours/week) Onsite work environment, Monday through Friday #J-18808-Ljbffr