Data Engineer I, AWS WW Field Enablement, Analytics and Product Operations
Job
Amazon.com, Inc.
Seattle, WA (In Person)
Full-Time
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Job Description
Description AWS Worldwide Field Enablement (WWFE) is looking for a Data Engineer helping us evolving our data infrastructure to next phase of providing insights through AI based solutions. You'll create data solutions that will optimize existing workflows providing better insights. You will have access to entire AWS AI stack to create next generation data solutions for AI based productivity tools and automation. AWS Global Sales drives adoption of the AWS cloud worldwide, enabling customers of all sizes to innovate and expand in the cloud. Our team empowers every customer to grow by providing tailored service, unmatched technology, and support. We dive deep to understand each customer's unique challenges, then craft innovative solutions that accelerate their success. This customer-first approach is how we built the world's most adopted cloud. Join us and help us grow. Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Key job responsibilities
- 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 (MapReduce, MPP architectures, NoSQL databases) About the team About AWS Diverse Experiences AWS values diverse experiences.
- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services. Basic Qualifications
- 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 Preferred Qualifications
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
- 4+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Knowledge of AWS Infrastructure
- Knowledge of BI analytics, reporting or visualization tools like Tableau, AWS QuickSight, Cognos or other third-party tools Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
- 101,300.00
- 160,000.
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