As a Data Engineer, you will partner with Business Intelligence Engineers and partner teams to build data pipelines and solutions to harness the vast amount of operational data from the AWS fleet. You will own the timely delivery of such data for use in downstream business intelligence solutions, as well as all necessary actions to ensure the reliability of data provided for business decision making. Data analysis is at the core Amazon's culture, and your work will have a direct impact on decision making and strategy for our organization.
The ideal candidates will have excellent analytical abilities, curiosity, and strong technical skills. They will have a strong bias toward data driven decision making, and building scalable data pipelines and systems to facilitate such decision making. They will be a self-starter; comfortable with ambiguity; able to think big and be creative, while exercising strong judgment and good instincts to be right a lot. The ideal candidate is motivated by delivering high-quality and innovative solutions within timeframes that most think are impossible. If you are excited about using data to look around corners and drive engineering solutions that are the foundation of AWS data centers, this role is for you!
Key job responsibilities
Collaborate with Business Intelligence Engineering team members, engineering stakeholders, partner technical teams, and business stakeholders, to gather business and functional requirements, and translate these requirements into a robust, scalable, and operable data infrastructure that works well within the overall AWS data architecture, and leads to improved engineering decisions.
Develop a deep understanding and awareness of operational data from the AWS fleet, and build mechanisms for retrieving and aggregating such data for use by downstream business intelligence solutions.
Develop a deep understanding of our vast data sources, and provide continuous recommendations for use to solve specific business problems.
Take ownership of data reliability by, among other things, performing deep-dives to find root causes of potential data anomalies, and taking subsequent action to address these anomalies.
Continuously optimize the performance of data queries, and address extract, transform, load (ETL) procedures.
Insist on the highest standards by recognizing and adopting best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.
BASIC 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 experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field
PREFERRED QUALIFICATIONS
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, GA, Atlanta - 132,100.00 - 178,800.00 USD annually
