Sr. Data Engineer, Strategic Customer Engagements (AWS)

Amazon Inc.; Seattle (WA); On-site; USD 155,000 - 209,000; Full time

Job summary

Amazon Web Services, Inc. in Seattle is seeking a Sr. Data Engineer to build and scale a data analytics platform for Strategic Customer Engagements, turning data into actionable insights for deal execution.

You will own end-to-end data pipelines, collaborate with Product Managers, BIEs, and business partners, and apply GenAI and AWS services to create AI-enabled data products. This high-visibility role requires strong communication, data architecture, and the ability to translate business

Qualifications

• 5+ years of data engineering experience.
• Experience with data modeling, warehousing and ETL pipelines.
• Experience with SQL and at least one programming language (Python/Java/Scala/NodeJS).
• Experience mentoring team members on best practices.

Responsibilities

• Build and maintain backend data infrastructure for analytical platforms and applications.
• Lead architectural improvements to simplify complex data systems and reduce bottlenecks.
• Translate business problems into technical data requirements with stakeholders.

Skills

Data engineering

Data modeling

SQL

Programming languages

Mentoring

Tools

Hadoop

Hive

Spark

EMR

Job description

Sr. Data Engineer, Strategic Customer Engagements

Job ID: 10439451 | Amazon Web Services, Inc.

Are you passionate about leveraging data to deliver actionable insights that impact the daily business decisions of AWS? Do you want to have an impact on making strategic deals come to life?

If so, we are looking for a Sr. Data Engineer to join the Strategic Customer Engagements team to develop a scalable data analytics platform. The Strategic Customer Engagements Deal Team works with our customers on commercial private pricing opportunities to meet their desired business outcomes while ensuring alignment with AWS business objectives.

In this role, you will be responsible for end-to-end development of data engineering solutions from the ground up. You should have expertise in the creation and management of datasets and the proven ability to translate data into meaningful insights through collaboration with Product Managers, Business Intelligence Engineers (BIEs), and business partners. You should be passionate about designing scalable analytics solutions for a fast-growing business.

This is a high-visibility role. The right candidate will possess excellent business and communication skills, be able to work with business owners to translate business problem statements into technical requirements. You should have a solid understanding of how to build efficient and scalable data infrastructure and data models. The role will leverage generative AI and AWS services to raise the bar on how the team consumes and acts on data and build the next generation of AI-enabled data platform.

Key Job Responsibilities

• Build and maintain backend data infrastructure for analytical platforms and applications, ensuring data is clean, fresh, and optimized for downstream consumption
• Lead architectural improvements that simplify complex data systems and transformations and proactively address deficiencies that create bottlenecks in the data infrastructure
• Translate business problem statements into technical data requirements, partnering with BIEs and product management and stakeholders to define what data products to build
• Ensure data quality through monitoring, validation, auditing, and documentation of pipelines and data sources
• Leverage AWS services and GenAI to build next-generation data solutions that improve efficiency and unlock new analytical capabilities
• Build data pipelines purpose-built for LLM consumption and create data products and feature stores that serve GenAI applications in near real-time
• Lead design reviews for your team's data architecture and actively participate in design reviews of related software and data systems

Basic Qualifications

• 5+ years of data engineering experience
• Experience with data modeling, warehousing and building ETL pipelines
• Experience with SQL
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
• Experience mentoring team members on best practices

Preferred Qualifications

• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
• Experience operating large data warehouses

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits .

USA, NY, New York - 170,000.00 - 230,000.00 USD annually

USA, VA, Arlington - 154,600.00 - 209,100.00 USD annually

USA, WA, Seattle - 154,600.00 - 209,100.00 USD annually

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Veterans, military spouses, and people with disabilities are encouraged to apply.