Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers that work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even image yet. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling and fun.
The Amazon Robotics Data Science & Data Engineering team discovers insights in vast and varied robotic data to help our engineering teams understand how their technologies operate across Amazon’s network of warehouses. We collaborate with designers, software and hardware engineers, and operations teams to understand product requirements, make feature trade-offs, design, and operate new applications of Amazon Robotics technology. We conduct relevant, insightful analysis and communicate the results through white papers and presentations. Our methods include design of experiments, statistical modeling, machine learning, financial analysis, and data visualization.
As an Amazon Robotics Data Engineer, you will be working in one of the world's largest data warehouse environments. We are passionate about building a highly scalable big data system to support our analytics, machine learning, and data applications and seek a engineer who can help build a technology development data platform, support the development of experimentation tools and setup pipelines for diagnostic and predictive models.
A successful candidate should have a background in business analytics, data science, data visualization, and data engineering. We are looking for jack-of-all-trades that are able to select and use the right tools to bring clarity to complex questions and help drive decisions. While we don’t assume mastery in all areas, successful team members can speak and work competently in multiple domains.
· Bachelors degree or higher in a quantitative/technical field (e.g. Computer Science, Statistics, Engineering)
· Design, creation, management, and business use of large datasets
· Proficiency in at least one modern programming language such as Java, Scala, or Python
· Knowledge of data management fundamentals and data storage principles
· Knowledge of distributed systems as it pertains to data storage and cloud computing
· Experience working with Open Source Big Data tools (Parquet, Spark, Hadoop, Presto)·
· Experience in working and delivering end-to-end projects independently
· Strong problem-solving skills and ability to prioritize conflicting requirements.
· Excellent written and verbal communication skills and ability to succinctly summarize key findings.
· Comfortable working as both part of a high-performing, diverse team and as an independent performer.
· Ability to multitask and prioritize critical tasks and conflicting requirements with a high attention to detail.
· 2+ years of relevant experience in one of the following areas: Data engineering, database engineering, business intelligence or business analytics
· Experience working with AWS Big Data Technologies (EMR, Redshift, S3)
· Proven track record of delivering a big data solution
· Experience working with both Batch and Real Time data processing systems
· 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 coding practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.