Data Engineer, Data Infrastructure and Generative Intelligence - AIGC Finance

Amazon’s AIGC DIGI team is seeking a Data Engineer to design and deliver analytical data infrastructure for multiple Amazon Ads businesses. The role partners with Finance and business stakeholders to create scalable, stable, and accurate data solutions while coordinating with engineering teams on ETL/ELT, data modeling, and warehousing.

Responsibilities

• Assess business needs and review the existing technology stack and data landscape; design, redesign, implement, and build analytical data infrastructure for multiple ads businesses.
• Align upstream and partner data teams to ensure reliable data solutions for the team.
• Manage AWS resources including EC2, EMR, S3, Glue, and Redshift.
• Collaborate with other technology teams to extract, transform, and load data from a wide variety of source systems.
• Explore and adopt the latest AWS technologies to add capabilities and improve efficiency.
• Work with and support Business Intelligence Engineers (BIEs) to apply best practices in reporting and analysis, including data integrity, test design, analysis, validation, and documentation.
• Translate business questions into requirements and build scalable data solutions with relevant stakeholders.
• Continuously improve reporting and analysis workflows by automating or simplifying self-service support for customers.

Required Qualifications

• 3+ years of data engineering experience.
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes.
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies.
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling.
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL.
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle.
• 3+ years of experience in the job offered or a related occupation.
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes.
• Bachelor’s degree (or foreign equivalent) in Computer Science, Engineering, Information Systems, Mathematics, or a related field.
• Experience with data modeling, warehousing, and building ETL pipelines.

Technologies

• AWS, EC2, EMR, S3, Glue, Redshift
• SQL, Oracle
• ETL, ELT
• OLAP, data modeling, ETL pipelines
• Kinesis, FireHose, Lambda
• IAM roles and permissions
• Non-relational databases and data stores, including object storage, document or key-value stores, graph databases, and column-family databases

Preferred Qualifications

• Experience with AWS technologies such as Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions.
• Experience with non-relational databases/data stores including object storage, document or key-value stores, graph databases, and column-family databases.

Compensation and Location

Location: New York, NY (onsite)

Salary: USD 145,300 to 196,600 per year

Benefits

• Sign-on payments
• Restricted stock units (RSUs)
• 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
• Parental leave

About the Team

The team builds and operates scalable data infrastructure and AI solutions for finance and business stakeholders across AIGC. This role works closely with the APM Advertising Finance team, which supports publishers including Stores, Amazon Business, Books, Grocery/Physical Store, Devices, Video, and Audio.

The team focuses on accelerating top-line revenue and improving profitability by evaluating ad supply monetization and utilization, product feature or sales package adoption, campaign performance, and other growth drivers.