Data Engineer, Alexa Shopping
- Perth, Australia
Do you want to reinvent shopping on Amazon? With ever expanding selection, and ambient computing looming on the horizon, it's time to create a new shopping experience, beyond search & browse, helping busy customers easily find low-regret products that meet their in-the-moment need. It's time to leverage big data and machine learning to generate relevant and trustworthy recommendations for billions of shopping journeys through billions of products, and to make it easy and natural for customers to discover those recommendations. We are seeking the industry's best to help us create new ways to interact, search and shop.
As a Data Engineer you will be working in one of the world's largest and most complex data warehouse environments using latest set of toolsets. We help product teams at Alexa Shopping build the future of shopping by providing metrics on new features and help them perform A/B testing which will act as feedback loop for voice user experience. Our team is responsible for mission critical analytical reports and metrics that are viewed at the highest levels in the organization. We are also working on near real time analytics using the latest set of tools for data visualization and investing in Big Data technologies. You should have deep expertise in the design, creation, management, and business use of extremely large datasets.
You should be highly analytical, have excellent communication skills, resourceful, customer focused, team oriented, and have an ability to work independently under time constraints to meet deadlines. You will be comfortable thinking big and diving deep. A proven track record in taking on end-to-end ownership and successfully delivering results in a fast-paced, dynamic business environment is strongly preferred. Above all you should be passionate about working with large data sets and someone who loves to bring datasets together to answer business questions and drive change.
• 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
• Proficiency in any programming language; preferably Python or Java.
• Expert knowledge of SQL and of relational database systems and concepts
• Expert knowledge of Data Modelling for OLAP databases and large scale distributed data platforms
• Experience with Hadoop/EMR, ETL pipeline tools and code version control systems like Git
• Strong written and verbal communication skills
• Comfortable working in a fast paced, highly collaborative, dynamic work environment
• Proficiency with Apache Spark with a general purpose programing language like Python, Java, Scala
• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience building large-scale, high-throughput, 24x7 data systems
• Strong attention to detail and desire to work in a collaborative, intellectually curious environment.
• Experience providing technical leadership and mentor other engineers for the best practices on the data engineering space
• Knowledge of batch and streaming data architectures like Kafka, Kinesis, Flink, Storm, Beam
• Familiarity with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
• Understanding of agile software development
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