- 1+ 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
- 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.)
- Experience working with AWS big data technologies (EMR, Redshift, S3, AWS Glue, Kinesis and Lambda for Serverless ETL)
- Knowledge of data management fundamentals and data storage principles
- Knowledge of distributed systems as it pertains to data storage and computing
- Hands-on experience and advanced knowledge of SQL
- Basic scripting skills using Python and Scala
- Basic understanding of Machine Learning
Have you ever thought about what it takes to detect and prevent fraudulent purchases among hundreds of millions of ecommerce transactions in six countries? What would you do to create a trusted marketplace where millions of buyers and sellers can safely transact online? What kinds of processes and systems would you build to maximize customer satisfaction?
Our mission in Payments Risk is to make Amazon.com the safest place to shop online. The Payments Risk team safeguards the order pipelines; monitoring, tracking, and managing risk to ensure long-term buyer satisfaction. The Payments Risk group designs and builds the software systems, risk models and operational processes that minimize risk and maximize trust in Amazon.com. In addition to this, we evaluate new business opportunities from across the company to determine how we can minimize the risk associated with these launches.
Amazon.com is seeking an outstanding Data Engineer to join the Payments Risk Analytics team. Amazon.com has culture of data-driven decision-making, and demands business intelligence that is timely, accurate, and actionable. If you join the Amazon.com Payments Risk team your work will have an immediate influence on day-to-day decision making at Amazon.com and drive the adoption of new Business Intelligence technologies.
Are you passionate about turning large amounts of information into knowledge? Are you passionate about building and leading data teams? Can you architect large data systems? Can you work with business partners and across technical teams?
A key responsibility of this role is to build large data systems that help us drive advanced analytics for Payments Risk. A successful candidate will be uncompromisingly detail oriented, efficient, and customer obsessed. Your work must be accurate, timely, and insightful. You must be a self-starter who is able to think big and work in a fast-paced and ever-changing environment. You will build sustainable and scalable analytics processes, and data systems that can be leveraged across Payments Risk.
As a Data Engineer on the Analytics team, you’ll have huge impact on how customers engage with Amazon through building infrastructure to answer questions with data, using software engineering best practices, data management fundamentals, and recent advances in distributed systems (i.e. MapReduce, noSQL databases). You will work with passionate scientists, business intelligence engineers, software development engineers and product managers, to deliver a variety of stable and performant data feeds used for developing business insights as well as offline machine learning use cases.
We love to work with smart people who have a strong sense of ownership and strong engineering mindset. You are a technical leader for your team and a great mentor. You provide perspective and context for technology choices. You’re up to the challenge of real-time notification strategies, latency, TPS and building an end-to-end platform that internal Amazon teams integrate with. You motivate your team to pursue ambiguous situations and rapidly produce prototypes for a more personalized experience. You outline paths from prototype to product. You deeply invest in each colleague's career growth, improving their technical knowledge, and defining your team's operational metrics.
- 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
- Demonstrated strength in data modeling, ETL development, and data warehousing
- Experience using business intelligence reporting tools (Quicksight, Tableau etc.)
- 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
- Mindset and analytical skills to towards continuous improvement and have an edge to always research on latest technologies
- Passion for building great notification experiences which directly impacts our customers