Sr. Data Engineer, Deal Tooling and Insights, Strategic Customer Engagements

Amazon Web Services, Inc. offers a compelling, onsite opportunity in Seattle, WA for a Sr. Data Engineer on the Strategic Customer Engagements team. The role provides a salary range of USD 154,600 to 209,100 per year and a path to influence strategic deals through scalable data analytics platforms. AWS emphasizes a collaborative culture and a robust benefits package designed to support you and your family.

Benefits

• Comprehensive health coverage including medical, dental, vision, and prescription, with Basic Life & AD&D insurance and options for supplemental life plans, plus Employee Assistance Program, mental health support, Medical Advice Line, Flexible Spending Accounts, and Adoption and Surrogacy Reimbursement.
• 401(k) with company matching
• Paid time off
• Parental leave
• Sign-on payments
• Restricted stock units (RSUs)

Responsibilities

• Develop and maintain the backend data infrastructure that underpins analytical platforms and applications, ensuring data is clean, current, and optimized for downstream use.
• Drive architectural improvements to simplify complex data systems and transformations while proactively removing bottlenecks in the data pipeline.
• Collaborate with business intelligence engineers, product management, and stakeholders to translate business problems into technical data requirements and define the data products to build.
• Establish data quality through monitoring, validation, auditing, and documenting data sources and pipelines.
• Leverage AWS services and GenAI to create next generation data solutions that boost efficiency and enable new analytics capabilities.
• Design pipelines tailored for LLM consumption and develop data products and feature stores to support GenAI applications in near real-time.
• Lead design reviews of the team's data architecture and contribute to design discussions of related software and data systems.

Requirements

• Minimum five years of data engineering experience.
• Experience with data modeling, data warehousing, and building ETL pipelines.
• Proficiency in SQL.
• Proficiency in at least one modern programming or scripting language such as Python, Java, Scala, or NodeJS.
• Experience mentoring teammates on data engineering best practices.

Technologies

• Python
• Java
• Scala
• NodeJS
• SQL
• Hadoop
• Hive
• Spark
• EMR
• AWS services
• GenAI
• LLM