As a Data Engineer you will be working in one of the world's largest and most complex data warehouse environments using latest set of toolsets. We help product teams at Alexa Shopping build the future of shopping by providing metrics on new features and help them perform A/B testing which will act as feedback loop for voice user experience. Our team is responsible for mission critical analytical reports and metrics that are viewed at the highest levels in the organization. We are also working on near real time analytics using the latest set of tools for data visualization and investing in Big Data technologies. You should have deep expertise in the design, creation, management, and business use of extremely large datasets.
The role offers a unique opportunity to build a new set of analytical experiences from the ground up. You should be highly analytical, have excellent communication skills, resourceful, customer focused, team oriented, and have an ability to work independently under time constraints to meet deadlines. You will be comfortable thinking big and diving deep. A proven track record in taking on end-to-end ownership and successfully delivering results in a fast-paced, dynamic business environment is strongly preferred. Above all you should be passionate about working with large data sets and someone who loves to bring datasets together to answer business questions and drive change.
Key job responsibilities
Design and develop the pipelines required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Python and AWS big data technologies.
Oversee and continually improve production operations, including optimizing data delivery, re-designing infrastructure for greater scalability, code deployments, bug fixes and overall release management and coordination.
Establish and maintain best practices for the design, development and support of data integration solutions, including documentation.
Work closely with Product teams, Data Scientists, Software developers and Business Intelligence Engineer to explore new data sources and deliver the data.
BASIC QUALIFICATIONS
- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
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)
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118,900/year in our lowest geographic market up to $205,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.