The Mkt Tech BI team at Amazon is responsible for managing one of the largest datasets, focusing on building a robust data infrastructure and automated reporting systems. The ideal candidate will work with large volumes of data and complex technical challenges, emphasizing data modeling, ETL design, and business intelligence tools. This role requires a self-starter who thrives in a fast-paced environment and enjoys collaborating with various stakeholders. The ultimate goal is to maximize Long Term Free Cash Flow through effective data solutions.

• 3+ years of data engineering experience
• 1+ years of experience developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes
• 1+ years of experience with OLAP technologies
• 1+ years of experience with data modeling
• 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
• Experience with big data technologies such as Hadoop, Hive, Spark, and EMR
• Experience with one or more scripting languages such as Python, KornShell, or Scala
• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience with non-relational databases or data stores
• Experience with AI/ML technologies

• Own the design, development, testing, deployment, and operation of data pipelines and datasets within an assigned domain
• Build and maintain scalable ETL/ELT workflows using SQL, Python, AWS services, and big data technologies
• Operate and improve data infrastructure, including Redshift clusters and data lake tables
• Improve operational reliability by identifying recurring failures and automating recovery steps
• Partner with various stakeholders to translate business and compliance requirements into scalable data solutions
• Build and operate conversational, self-service, and agentic analytics data products
• Contribute to data foundations that support forecasting, experimentation, and self-service analytics
• Implement data validation, lineage, documentation, and operational mechanisms
• Drive scoped modernization efforts such as pipeline simplification and automation
• Clarify ambiguous requirements and identify data quality gaps
• Mentor junior engineers on technical tasks and coding standards
• Participate in on-call and product support for business-critical pipelines
• Own the design and operation of data foundations that power GenAI and agentic analytics
• Build guardrails and evaluation mechanisms for AI-generated outputs
• Apply AI coding assistants and share effective patterns with the team

• Employees at Amazon are often offered comprehensive health benefits—including multiple medical plan options (no pre-existing condition exclusions, 100% covered in-network preventive care), dental and vision plans, a 24/7 medical advice line from day one, expert second-opinion services, and broad mental-health support with several free counseling sessions (including pediatric). Financial wellness typically includes a 401(k) with company match (up to 2%), Restricted Stock Units (equity), FSAs, an emergency savings program, product and partner discounts, and even college-savings and home-purchase programs. Overall, the package is designed to support employees and their families’ health, finances, and day-to-day life.