AI Data Engineer – Platform & Analytics
Analytics
Apache Airflow
Artificial Intelligence
Automation
Big Data
Bigdata
Cloud
Cloud Platform
Data
Data Analysis
Data Analytics
Data Architecture
Data Build Tool
Data Engineer
Data Integration
Data Lake
Data Lakehouse
Data Management
Data Modeling
Data Pipeline
Data Pipelines
Data Platform
Data Processing
Database
Databases
Databricks
Engineer
ETL
Iceberg
Large Language Models
Machine Learning
Snowflake
Spark
SQL
Job Description
AMD seeks an AI Data Engineer to design a medallion data lakehouse and end-to-end pipelines for manufacturing, IoT, and yield analysis data, leveraging AI tooling to accelerate development across multiple engines.
Responsibilities
- Architect and maintain a scalable medallion data lakehouse structure with Bronze, Silver, and Gold layers using Apache Iceberg.
- Construct and optimize curated Gold-layer data products for high‑performance consumption across an open ecosystem of engines including Snowflake, Databricks (Spark), Trino/Starburst, AWS Athena, and Presto.
- Design, develop, and manage complex, resilient data workflows and DAGs with Apache Airflow.
- Build, deploy, and monitor end-to-end ETL/ELT pipelines to ingest diverse semiconductor data streams into the data lake.
- Model data to enable high‑performance consumption, delivering clean, transformed, production‑ready datasets.
- Write and tune highly optimized SQL queries for transformation, analysis, and performance benchmarking.
- Leverage generative AI coding assistants and automation tools to speed up pipeline development, documentation, and testing.
- Implement data governance practices, data quality checks, and schema evolution rules within Iceberg and Snowflake environments.
Requirements
- Demonstrated experience in software, data engineering, and data management.
- Hands-on expertise scheduling and monitoring production-grade pipelines with Apache Airflow.
- Proven ability to design medallion architectures and extensive experience with Apache Iceberg.
- Advanced proficiency with Snowflake and hands-on experience building transformation models in DBT Core.
- Expert level SQL and Python knowledge with mastery of modern ETL/ELT patterns and design principles.
- Ability to write high quality code with keen attention to detail.
- Experience with modern concurrent programming and threading APIs.
- Experience with software development processes and tools such as debuggers, GitHub, and profilers is a plus.
- Demonstrated use of AI tooling to accelerate development, including GitHub Copilot, Snowflake Cortex, LLM APIs, Claude Code, and related platforms.
- Proven track record delivering multiple enterprise-grade, production-level, end-to-end data pipeline solutions from scratch.
Technologies
- Apache Iceberg
- Snowflake
- Databricks (Spark)
- Trino/Starburst
- AWS Athena
- Presto
- Apache Airflow
- DBT Core
- SQL
- Python
- GitHub Copilot
- Snowflake Cortex
- LLM APIs
- Claude Code
Academic Credentials
- BS Degree in Engineering or related field
Location
- Santa Clara, CA (onsite)
- Austin
- Seattle
- Secaucus
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