THE ROLE:

Join AMD as a Data Analytics Engineer and become part of a team that is shaping the future of data-driven decision-making. In this role, you will design and build scalable data pipelines, implement advanced analytics solutions, and leverage AI-driven tools to transform raw data into actionable insights. You’ll collaborate with product engineering teams and business stakeholders, working in a fast-paced environment that values innovation and continuous learning. This is an opportunity to work with cutting-edge technologies like Snowflake, DBT, and AI-powered analytics platforms, while contributing to AMD’s mission of advancing computing experiences globally.

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THE PERSON:

You are a detail-oriented, analytical thinker who thrives on solving complex data challenges. You have strong communication skills and enjoy collaborating across teams to deliver impactful solutions. Adaptability, curiosity, and a passion for leveraging technology to uncover insights are key traits for success in this role. You are proactive, organized, and capable of balancing multiple priorities while maintaining a focus on quality and innovation.

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KEY RESPONSIBILITIES:

• Design, develop, and maintain robust data pipelines and ETL processes, championing data modeling using DBT.
• Implement data models and structures in Snowflake for efficient data retrieval and analysis.
• Collaborate with engineering teams and business stakeholders to understand requirements and deliver analytics solutions.
• Develop and optimize SQL queries and scripts for data extraction and transformation.
• Ensure data quality and integrity through validation and cleansing processes.
• Create and maintain documentation for data processes, models, and analytics solutions.
• Monitor and troubleshoot data pipelines and analytics systems for optimal performance.
• Utilize visualization and AI-driven analytics tools (Power BI, ThoughtSpot, etc.) to enable natural language data interaction.
• Stay current with industry trends, AI-driven tools, and semantic modeling techniques.

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PREFERRED EXPERIENCE:

• Proficiency in SQL and relational databases (e.g., MsSQL, Oracle).
• Experience with Snowflake and data warehousing solutions.
• Familiarity with ETL/ELT platforms (DBT, Informatica) and data catalog tools (Lightup, Alation).
• Strong programming skills in Python or R for data manipulation and analysis.
• Knowledge of AI-driven analytics platforms, semantic modeling, and NLP techniques.
• Experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) and AI model deployment.
• Understanding of data governance and security best practices.

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ACADEMIC CREDENTIALS:

• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field preferred.
• Master’s degree is a plus.

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