Data Engineer , AWS WW Field Enablement, Analytics and Product Operations

Overview

AWS Worldwide Field Enablement (WWFE) is looking for a Data Engineer to evolve our data infrastructure to provide insights through AI-based solutions. You ll create data solutions that optimize existing workflows and provide better insights. You will have access to the AWS AI stack to create next-generation data solutions for AI-based productivity tools and automation.

• Design, build, and optimize logical data models and data pipelines for complex datasets
• Own ongoing data quality and create self-service access to datasets for business intelligence, AI-based tools and Model Context Protocols (MCP)
• Improve metadata for better AI results
• Collaborate with Program Managers, Technical Program Managers and other Data Engineers to design stable, performant data solutions
• Write secure, stable, testable, and maintainable code with minimal defects
• Apply appropriate data design approaches and make judicious trade-offs without over-engineering
• Optimize resource usage including system hardware, data storage, query optimization, and AWS infrastructure
• Participate actively in code reviews, design discussions, and team planning
• Resolve root causes of complex problems and balance customer requirements with team needs
• Stay current on distributed systems technologies (Map Reduce, MPP architectures, No
  
  SQL databases)

• 2+ years of data engineering experience
• Experience with data modeling, warehousing and building ETL pipelines
• Bachelor s degree or above in a quantitative/technical field such as computer science, engineering, statistics
• Knowledge of basics of designing and implementing a data schema like normalization, relational model vs dimensional model
• Knowledge of software engineering best practices across the development life cycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations

• Experience with big data technologies such as Hadoop, Hive, Spark, EMR
• Experience with ETL tools like Informatica, ODI, SSIS, BODI, Datastage, etc.
• 4+ years of analyzing and interpreting data with Redshift, Oracle, No
  
  SQL, etc.
• Knowledge of AWS Infrastructure
• Knowledge of BI analytics, reporting or visualization tools like Tableau, AWS Quick Sight, Cognos or other third-party tools

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