As a Data Engineer at OpsTech, you will build and evolve scalable data platforms that power analytics, machine learning, and AI-driven experiences across Amazon's global operations. Your role will involve designing high-performance data pipelines and creating trusted data products that transform complex operational data into actionable intelligence. You will collaborate with various teams to improve data quality and reliability while exploring emerging data and AI technologies. This position offers significant opportunities for technical growth and influence in shaping the future of data capabilities at Amazon.

• 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
• 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 Python in a data engineering environment, including building data processing pipelines, automation, and testing
• 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 such as object storage, document or key-value stores, graph databases, and column-family databases
• Knowledge of professional software engineering best practices for the full software development life cycle

• Build scalable data pipelines and platforms that transform complex operational data into trusted, AI-ready data products.
• Power AI agents, machine learning systems, and intelligent automation with reliable data, context, and semantic layers.
• Develop batch and streaming architectures that deliver timely operational signals for analytics, detection, diagnosis, and decision making.
• Create reusable datasets and data products that support analytics, experimentation, production models, and operational applications.
• Build feature pipelines, training datasets, and production workflows that connect data engineering with machine learning and AI.
• Improve platform reliability through automated data quality, observability, lineage, testing, and anomaly detection.
• Design semantic models and metrics that provide a consistent understanding of the business for operators, leaders, analysts, and AI systems.
• Partner with Data Scientists, ML Engineers, Business Intelligence Engineers, Solution Architects, Program Managers, and operations teams to deliver measurable business impact.
• Raise the engineering bar by improving scalability, maintainability, governance, and development standards across OpsTech.
• Explore emerging data and AI technologies to help shape the next generation of OpsTech data platforms.

• 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.