Lead AI Data Engineer – Platform & Analytics
About The Position
At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career. We are seeking a Senior Data Engineer to design, build, and optimize our next-generation data platform for high-tech semiconductor operations. You will lead the implementation of a modern data lake, leveraging medallion architecture using Apache Iceberg, Snowflake, Databricks, and DBT Core, while using Airflow to orchestrate complex data workflows. In this role, you will own multiple end-to-end data pipeline solutions handling massive manufacturing, IoT, and yield-analysis data streams. We value innovation, so you will actively leverage AI engineering tools to accelerate development, automate code generation, and ensure rapid implementation turnarounds.
Requirements
- dedicated experience in software, data engineering and data management.
- Strong hands-on experience scheduling and monitoring production-grade pipelines with Apache Airflow.
- Proven track record of designing medallion architectures and working extensively with the Apache Iceberg table format.
- Advanced proficiency with Snowflake and deep hands-on experience building transformation models in DBT Core.
- Expert-level SQL & Python knowledge and complete 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, source code control systems (GitHub) and profilers is a plus
- Demonstrated experience using AI tools (e.g., GitHub Copilot, Snowflake Cortex, LLM APIs, Claude Code, etc.) to speed up code development and problem-solving.
- Experience delivering multiple enterprise-grade, production-level, end-to-end data pipeline solutions from scratch.
Responsibilities
- Architecture & Design: Architect and maintain a scalable medallion data lake house structure (Bronze, Silver, Gold layers) utilizing Apache Iceberg table formats.
- Multi-Engine Data Consumption: Build and optimize curated, semantic Gold-layer data products designed for seamless, high-performance consumption across an open ecosystem of multiple compute and query engines – including Snowflake, Databricks (Spark), Trino/Starburst, AWS Athena, and Presto.
- Pipeline Orchestration: Design, develop, and manage complex, resilient data workflows and DAGs using Apache Airflow.
- Pipeline Development: Build, deploy, and monitor robust end-to-end ETL/ELT pipelines to ingest diverse semiconductor data streams into the data lake.
- Data Modeling: Design and implement high-performance consumption data models, ensuring clean, transformed, and production-ready datasets.
- SQL Optimization: Write and tune complex, highly optimized SQL queries for data transformation, analysis, and performance benchmarking.
- AI-Driven Delivery: Utilize generative AI coding assistants and automation tools to accelerate pipeline development, documentation, and testing.
- Data Governance: Implement data quality checks, schema evolution rules, and governance practices inherent to Iceberg and Snowflake environments.
Benefits
- AMD benefits at a glance.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
