Looking for startup culture, high impact problems to solve and opportunities to grow?
Do you want to work in a well-funded startup in AWS on a game changer? AWS WW Revenue Organization (WWRO) is responsible to products and programs to enable AWS sellers become effective quickly. Our technologies have direct impact on the AWS' top line! We are building a recommendation engine that will take data from multiple desperate source and make sense of it.
Scope of Impact & Influence
You will work with a team of scientists and engineers on variety of machine learning use cases and help the team unlock value from data. Key responsibilities include
• Data modeling to support machine learning model training and offline, batch inference workflows.
• Build data pipelines to feed machine learning models for real-time and large-scale offline use cases.
• Work closely with machine learning and data scientists to scale model training, explore new data sources and feature extraction.
Mentoring & Career Growth
Our team is committed to supporting new team members. We have a broad mix of experience levels and Amazon tenures. We prioritize thought diversity and have regular meetings within the team to collect ideas from all roles.
Our team is diverse and geographically distributed. We understand that work-life balance is important. We offer some flexibility in how you structure your work to suit your other life commitments while adhering to core office working hours.
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon's culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust
Location: This role open to these locations: Seattle & Dallas. Relocation offered from within the US to any of these locations.
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have twelve employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon's culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Our team puts a high value on work-life balance. It isn't about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.
• 3+ years of experience as a Data Engineer or in a similar role
• Experience with data modeling, data warehousing, and building ETL pipelines
• Experience in SQL
• Bachelor's degree in computer science, engineering, mathematics, or a related technical discipline
• 4+ years of industry experience in software development, data engineering, business intelligence, data science, or related field with a track record of manipulating, processing, and extracting value from large datasets
• Experience using big data technologies (Hadoop, Hive, Hbase, Spark, EMR, etc.)
• Knowledge of data management fundamentals and data storage principles
• Knowledge of distributed systems as it pertains to data storage and computing
• 5+ years of experience as a Data Engineer, BI Engineer, Business/Financial Analyst or Systems Analyst in a company with large, complex data sources.
• Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
• Experience working with AWS big data technologies (EMR, Redshift, S3)
• Demonstrated strength in data modeling, ETL development, and data warehousing
• Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy
• Experience providing technical leadership and mentoring other engineers for best practices on data engineering
• Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the bias of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit: https://www.amazon.jobs/en/disability/us.