Amazon IN Platform Development team is looking to hire a Data Engineer to build for pan Amazon India businesses.
Amazon India is at the core of hustle @ Amazon WW today and the team is charted with democratizing data access for the entire marketplace & add productivity. The Data Engineer will play a key role in contributing to the success of each focus area, by partnering with respective business owners and leveraging data to identify areas of improvement & optimization. The role sits in the sweet spot between technology and business worlds AND provides opportunity for growth, high business impact and working with seasoned business leaders.
An ideal candidate will be someone with sound technical background in data domain – storage / processing / analytics, has solid business acumen and a robust automation / solution oriented thought process. Design, implement and support an data infrastructure for analytics needs of large organization
Adopt and drive AI-native practices while building data solutions. Build AI-powered products for business requirements
Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using Redshift SQL, Spark SQL and other AWS big data technologies
Optimize data pipelines,
build and manage Python-based automations/tools for data pipelines
Be enthusiastic about building deep domain knowledge about Amazon's business
Must possess strong verbal and written communication skills, be self-driven, and deliver high quality results in a fast-paced environment
Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency
5+ years of data engineering experience
Experience with data modeling, warehousing and building ETL pipelines
Experience with SQL
Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
Experience mentoring team members on best practices
Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
Experience operating large data warehouses
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