Data Engineer I, Data Engineering India

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Description

IN Data Engineering & Analytics(IDEA) Team is looking to hire a rock star Data Engineer to build data pipelines and enable ML models 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 performing data extraction, data transformation, building and managing data pipelines to ensure data availability for ML & LLM models of 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 working with SQL, Scripting (Python, typescript, javascript), databases, ML/LLM models, big data technologies such as Apache Spark (Pyspark, Spark SQL). An ideal candidate will be someone who is a self-starter that can start with a 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

• Build end to end data extraction, data transformation and data pipelines to ensure data availability for ML & LLM models that are critical to IN businesses.
• Enable ML/LLM tools by setting up all the required underlying data infrastructure, data pipelines and permissions to generate training and inference data for the ML models.
• Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL, Scripting and Amazon/AWS big data technologies
• Must possess strong verbal and written communication skills, be self-driven, and deliver high quality results in a fast-paced environment.
• Drive operational excellence strongly and build automation and mechanisms to reduce operations
• 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.

Basic Qualifications

• 2+ years of data engineering experience
• Experience with SQL
• Experience with one or more scripting language (e.g., Python, KornShell)
• Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
  
  

Preferred Qualifications

• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
• Knowledge of computer science fundamentals such as object-oriented design, operating systems, algorithms, data structures, and complexity analysis
  
  

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