Senior AI Automation Data Engineer

Our vision is to transform how the world uses information to enrich life for all.

Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.

About our Team:

Micron’s AI Automation and Data Engineering team drives enterprise data strategy and innovation by delivering scalable data platforms that power advanced analytics, artificial intelligence, and business automation. The team partners across engineering, operations, and business functions to modernize data ecosystems and enable data-driven decision making.

Position Overview:

Micron is seeking a Senior AI Automation Data Engineer to design, build, and scale modern enterprise data platforms that support AI, automation, analytics, and digital transformation initiatives. This role will focus on cloud-based data solutions, enterprise data modernization, and the development of secure, governed, and AI-ready data products!

Responsibilities:

• Design, develop, and maintain scalable data pipelines and integration frameworks for structured and unstructured data.
• Build and optimize cloud-based data solutions using Snowflake and AWS and/or GCP technologies.
• Lead modernization efforts by migrating legacy data platforms and implementing ETL/ELT architectures.
• Develop AI-ready datasets and data products that enable analytics, machine learning, generative AI, and automation initiatives.
• Establish data governance, security, monitoring, and CI/CD standard processes to ensure reliable and compliant data platforms.

Minimum Qualifications:

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related technical field.
• 5+ years of professional experience in data engineering, data platform development, or related subject areas.
• 3+ years of experience working with cloud-based data ecosystems and enterprise-scale data environments.
• Hands-on experience with Snowflake, AWS and/or GCP, SQL, and Python in production environments.
• Experience designing ETL/ELT pipelines, implementing data warehousing solutions, and applying CI/CD and Infrastructure-as-Code methodologies.

Preferred Qualifications:

• Experience implementing modern data architectures such as Data Fabric, Data Mesh, or similar frameworks.
• Experience supporting AI, machine learning, generative AI, or retrieval-augmented generation (RAG) solutions.
• Hands-on experience with at least one of the following: dbt, Apache Airflow, Databricks, Apache Spark, Kafka, BigQuery, or Redshift.
• Experience working with vector databases, semantic search, knowledge graphs, or enterprise search technologies.