Data Engineer I, IN Data Engineering & Analytics

Overview

- 1+ years of data engineering experience - Experience with SQL - Experience with data modeling, warehousing and building ETL pipelines - Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) - Experience with one or more scripting language (e.g., Python, KornShell)
IN Data Engineering & Analytics(IDEA) Team is looking to hire a rock star Data Engineer to build and manage the largest petabyte-scale data infrastructure in India for Amazon India businesses. IN Data Engineering & Analytics (IDEA) team is the central Data engineering and Analytics team for all A.in businesses. The team's charter includes 1) Providing Unified Data and Analytics Infrastructure (UDAI) for all A.in teams which includes central Petabyte-scale Redshift data warehouse, analytics infrastructure and frameworks for visualizing and automating generation of reports & insights and self-service data applications for ingesting, storing, discovering, processing & querying of the data 2) Providing business specific data solutions for various business streams like Payments, Finance, Consumer & Delivery Experience. The Data Engineer will play a key role in being a strong owner of our Data Platform. He/she will own and build data pipelines, automations and solutions to ensure the availability, system efficiency, IMR efficiency, scaling, expansion, operations and compliance of the data platform that serves 200 + IN businesses. The role sits in the heart of technology & 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 managing large data infrastructures, working with petabyte-scale data, building scalable data solutions/automations and driving operational excellence. An ideal candidate will be someone who is a self-starter that can start with a Platform requirement & work backwards to conceive and devise best possible solution, a good communicator while driving customer interactions, a passionate learner of new technology when the need arises, a strong owner of every deliverable in the team, obsessed with customer delight, business impact and ‘gets work done’ in business time. Key job responsibilities 1. Design/implement automation and manage our massive data infrastructure to scale for the analytics needs of Amazon IN. 2. Build solutions to achieve BAA(Best At Amazon) standards for system efficiency, IMR efficiency, data availability, consistency & compliance. 3. Enable efficient data exploration, experimentation of large datasets on our data platform and implement data access control mechanisms for stand-alone datasets 4. Design and implement scalable and cost effective data infrastructure to enable Non-IN(Emerging Marketplaces and WW) use cases on our data platform 5. Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL, Amazon and AWS big data technologies 6. Must possess strong verbal and written communication skills, be self-driven, and deliver high quality results in a fast-paced environment. 7. Drive operational excellence strongly within the team and build automation and mechanisms to reduce operations 8. Enjoy working closely with your peers in a group of very smart and talented engineers. A day in the life India Data Engineering and Analytics (IDEA) team is central data engineering team for Amazon India. Our vision is to simplify and accelerate data driven decision making for Amazon India by providing cost effective, easy & timely access to high quality data. We achieve this by providing UDAI (Unified Data & Analytics Infrastructure for Amazon India) which serves as a central data platform and provides data engineering infrastructure, ready to use datasets and self-service reporting capabilities. Our core responsibilities towards India marketplace include a) providing systems(infrastructure) & workflows that allow ingestion, storage, processing and querying of data b) building ready-to-use datasets for easy and faster access to the data c) automating standard business analysis / reporting/ dash-boarding d) empowering business with self-service tools to manage data and generate insights.