Benefits
- 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
- Parental leave
- Sign-on payments
- Restricted stock units (RSUs)
About the team
This team provides data engineering and business intelligence engineering services to the rest of MOTOR. We are the data experts behind the scenes helping the operational teams focus on operations by ensuring they have accurate, timely data and provide business insights to help improve operational excellence.
Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and continue to innovate, which is why customers from startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Diverse Experiences
Amazon values diverse experiences. If you do not meet all of the preferred qualifications and skills listed, we encourage you to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Work Life Balance
We value work-life harmony. Flexibility is part of our culture to support both professional and personal commitments, enabling success in the cloud.
Inclusive Team Culture
AWS emphasizes learning and curiosity. Employee‑led affinity groups foster inclusion and pride in our differences. Ongoing events and learning experiences, including CORE and AmazeCon conferences, inspire us to embrace our uniqueness.
Mentorship and Career Growth
We continuously raise our performance bar and provide knowledge-sharing, mentorship and career-advancing resources to help you develop into a well‑rounded professional.
Responsibilities
- Build and maintain the infrastructure to answer questions with data, using software engineering best practices, data management fundamentals, data storage principles, recent advances in distributed systems, and operational excellence best practices. Build datasets that analysts and scientists use to generate actionable insights.
- Define the data engineering processes that leverage various AWS services to improve accessibility, redundancy, data integrity, cost, and storage requirements.
- Develop high quality solutions for the faster development of the products/models that solve the business needs in a scalable format, while also anticipating future requirements.
- Collaborate with Research/Applied Scientists, Data Engineers, Business Intelligence Engineers, Data Scientists, Business Analysts, and Product/Program Managers to understand the business and technical requirements, and make decisions that help make the products/programs smoother.
- Interface with other technology/data engineering teams to extract, transform, and load data from a wide variety of data sources using and AWS data technologies.
- Lead the technical design and implementation of the data infrastructure.
- Design and manage data audit, quality, and reconciliation processes in collaboration with various stakeholders.
Requirements
- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with CI/CD pipelines build processes
- Experience in one or more scripting languages (e.g., Python, Ruby, Perl)
- Experience working with Git or an equivalent distributed version control system
- 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)
- Experience developing, deploying and managing AI products at scale
Technologies
- Python
- Ruby
- Perl
- Git
- Redshift
- S3
- AWS Glue
- EMR
- Kinesis
- FireHose
- Lambda
- IAM
