Data Engineer, IN Data Engineering & Analytics

Amazon Business; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Amazon IN Platform Development team is hiring a rock‑star Data/BI Engineer to build for pan Amazon India businesses. You will design and implement data infrastructure for analytics, optimize pipelines, and partner with business owners to deliver scalable insights.

Ideal candidates have 3+ years in data engineering, strong SQL, ETL, and experience with AWS data services like Redshift, S3, Glue, EMR, and Kinesis. This role blends technology and business impact with high ownership and collaboration.

Qualifications

• 3+ years of data engineering experience.
• Experience with SQL and data warehousing.
• Experience building ETL pipelines and data models.

Responsibilities

• Design, implement and support data infrastructure for analytics needs.
• Adopt AI-native practices while building data solutions.
• Interface with other teams to extract and load data from diverse sources using AWS tech.
• Optimize data pipelines and build Python-based automations.
• Gain domain knowledge of Amazon's business.
• Communicate clearly with peers and stakeholders.
• Automate reporting and self-service analytics for customers.
• Explore new AWS technologies to add capabilities.

Skills

SQL

Data modeling

ETL pipelines

Python/Java/Scala

Data engineering

Tools

Redshift

S3

AWS Glue

EMR

Kinesis

Lambda

IAM

Job description

DescriptionAmazon IN Platform Development team is looking to hire a rock star Data/BI Engineer to build for pan Amazon India businesses.

DescriptionAmazon IN Platform Development team is looking to hire a rock star Data/BI 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. That translates to owning the processing of every Amazon India transaction, for which the team is organized to have dedicated business owners & processes for each focus area. 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. He / She will build deliverables like business process automation, payment behavior analysis, campaign analysis, fingertip metrics, failure prediction etc. that provide edge to business decision making AND can scale with growth. 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 strong automation / solution oriented thought process. Will be a self-starter who can start with a business problem and work backwards to conceive & devise best possible solution. Is a great communicator and at ease on partnering with business owners and other internal / external teams. Can explore newer technology options, if need be, and has a high sense of ownership over every deliverable by the team. Is constantly obsessed with customer delight & business impact / end result and ‘gets it done’ in business time.

Key job responsibilities

• 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
• Enjoy working closely with your peers, stakeholders and customers.
• 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

About The Team

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 building 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) & products that allow ingestion, storage, processing and querying of data b) building AI-powered products to transform the data space c) building ready-to-use datasets for easy and faster access to the data d) automating standard business analysis / reporting/ dashboarding e) empowering business with self-service AI and non-AI tools for deep dives & insights seeking.

Basic Qualifications

• 3+ years of data engineering experience
• Experience with SQL
• Experience with data modeling, warehousing and building ETL pipelines
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
• Experience as a data engineer or related specialty (e.g., software engineer, business intelligence engineer, data scientist) with a track record of manipulating, processing, and extracting value from large datasets

Preferred Qualifications

• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
• Experience working on and delivering end to end projects independently
• Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

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