Community Trust is responsible for building customer trust and reducing abuse on Amazon’s Community features, including Customer Reviews, Questions and Answers, Lists, Spark and Customer Profiles. By driving customer trust in user generated content, we increase long term customer engagement on Amazon. Upholding customer trust is multifaceted but impactful for Amazon. Our team is passionate about human motivation and behavior and uses business intelligence, machine learning, classification algorithms and scalable platform services to have a cross-org impact every day. We are inherently scrappy and innovative, experimenting with data about millions of contributions worldwide to identify new genuine and malicious content and contribution patterns. We evaluate user research, customer experience knowledge, data, and cross-Amazon abuse expertise to ensure other teams think about customer trust.
The role requires customer focus, creativity, a data-first orientation and experience with performance and scale. You will have the opportunity to make a difference in a fast paced, dynamic environment where your ability to deep dive, communicate, collaborate and drive changes will be a key. You will play a very important role in ensuring a great customer experience improving customer trust in our user generated content features with an eye on automation to help developing scalable and robust solutions.
As a data engineer on this team, you will have the exciting opportunity to work on very large data sets in one of the world’s largest and most complex data warehouse environments. You will work closely with scientists, engineers, analysts and business teams to design solutions for their respective needs, which will require creativity and strong problem solving skills. You will own data engineering roadmap efforts, guiding and partnering with software engineers in building platforms to solve complex problems in efficient and scalable ways. This role will work backwards from customer problems to design solutions to meet the goals.
You should have excellent communication skills to be able to work with a variety of people with different background to build data solutions that can answer their questions. You own customer relationship about data and execute tasks that are manifestations of such ownership, like ensuring high data availability, low latency, documenting data details and transformations and handling user notifications and training.
· Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field and 7+ years industry experience.
· 5+ years of hands-on experience in writing complex, highly-optimized SQL queries across large data sets.
· 2+ years of experience in scripting languages like Python etc.
· Demonstrated strength in data modeling, ETL development, and Data warehousing.
· Experience in working and delivering end-to-end projects independently.
· Knowledge of distributed systems as it pertains to data storage and computing
· Experience building data products incrementally and integrating and managing datasets from multiple sources.
· Knowledge of professional software engineering practices and best practices for the full software development life cycle, including coding standards, code reviews, source control management, testing, and operations.
· Experience with AWS Tools and Technologies (Redshift, S3, EC2).
· Working knowledge of software development methodologies like Agile or Waterfall.
· Strong customer focus, ownership, urgency and drive.
· Excellent communication skills and the ability to work well in a team.
· Effective analytical, troubleshooting and problem-solving skills.
· Graduate degree in Computer Science, Engineering or related technical field.
· 10+ years of DW experience.
· Experience with Big Data Technologies (Hadoop, Hive, Hbase, Pig, Spark, etc.)
· Developing and deploying datamart, analytic solutions.
· Experience using Linux/UNIX to process large data sets.
· Experience providing technical leadership and mentor other engineers for data engineering best practices.
· Advanced knowledge and expertise with Data modelling skills, Advanced SQL with Oracle, MySQL, and Columnar Databases.
· Demonstrated industry leadership in the fields of Database and/or Data Warehousing, Data Sciences and Big Data processing.
· Strong communication skills – both written and verbal.
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