Senior Data Engineer, AWS Specialist and Partner Organization

About the role

The Senior Data Engineer, AWS Specialist and Partner Organization plays a crucial role in supporting the data needs of the AWS Specialist and Partner Organization. This team works closely with millions of customers globally to help them transform their businesses using AWS's Core, GenAI, and Partner services and solutions.

Responsibilities

• Expertise with SQL, ETL, and data wrangling, with experience in cloud-based data services like AWS EMR, Glue, Firehose, Lambda, and similar technologies.
• Hands-on experience with AI/ML technologies, including large language models (LLMs), and a strong understanding of designing and building Agentic Frameworks.
• Comfortable with ambiguity in a fast-paced and ever-changing environment, capable of thinking big while paying close attention to detail.
• Passionate about working with huge data sets, leveraging AI-driven approaches to unlock insights, and bringing data together to answer business questions and drive growth.

Requirements

• 5+ years of data engineering experience.
• Experience with data modeling, warehousing, and building ETL pipelines.
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS.
• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions.
• Experience in writing complex, highly-optimized SQL queries across large datasets.

Preferred Qualifications

• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR.
• Experience operating large data warehouses.
• Experience delivering results for large, cross-functional initiatives/projects.
• Experience providing technical leadership and mentoring other engineers for best practices on data engineering.
• Experience with AI/ML technologies, including Agentic Frameworks, autonomous agents, multi-agent orchestration, tool integration, and RAG pipelines.
• Experience driving technical vision and roadmap for data platforms and infrastructure.

Qualifications

• Basic Qualifications: 5+ years of data engineering experience, experience with data modeling, warehousing, and building ETL pipelines, experience in at least one modern scripting or programming language, experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions, experience in writing complex, highly-optimized SQL queries across large datasets.
• Preferred Qualifications: Experience with big data technologies such as: Hadoop, Hive, Spark, EMR, experience operating large data warehouses, experience delivering results for large, cross-functional initiatives/projects, experience providing technical leadership and mentoring other engineers for best practices on data engineering, experience with AI/ML technologies, including Agentic Frameworks, autonomous agents, multi-agent orchestration, tool integration, and RAG pipelines, experience driving technical vision and roadmap for data platforms and infrastructure.

Pay

Base salary range for this position is listed below. Final compensation will be determined based on factors including experience, qualifications, and location.

• USA, CA, Mountain View - $177,800.00 - $240,500.00 USD annually
• USA, CA, San Francisco - $177,800.00 - $240,500.00 USD annually
• USA, NY, New York - $170,000.00 - $230,000.00 USD annually
• USA, TX, Austin - $154,600.00 - $209,100.00 USD annually
• USA, TX, Dallas - $154,600.00 - $209,100.00 USD annually
• USA, WA, Seattle - $154,600.00 - $209,100.00 USD annually