Senior Data Engineer
Role details
Job location
Tech stack
Job description
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.
Key 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., AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD's "Responsible AI Policy" is available here.
Requirements
dedicated experience in software, data engineering and data management.
- Workflow Orchestration
Strong hands-on experience scheduling and monitoring production-grade pipelines with Apache Airflow.
- Lakehouse Expertise
Proven track record of designing medallion architectures and working extensively with the Apache Iceberg table format.
- Tech Stack Mastery
Advanced proficiency with Snowflake and deep hands-on experience building transformation models in DBT Core.
-
Core Skills
-
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
AI Tooling
Demonstrated experience using AI tools (e.g., GitHub Copilot, Snowflake Cortex, LLM APIs, Claude Code, etc.) to speed up code development and problem-solving.
Problem Solving
Experience delivering multiple enterprise-grade, production-level, end-to-end data pipeline solutions from scratch.
ACADEMIC CREDENTIALS
- BS Degree in Engineering or related field