Data Engineer II, Sales Data Services (SDS) (Advertising)

Amazon; Bengaluru; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

Amazon Advertising is seeking a Data Engineer II to design and optimize data warehouse and data lake infrastructure on AWS, enabling scalable analytics for SDS customers and internal stakeholders.

You will build and maintain ETL pipelines, collaborate across teams, mentor peers, and empower users with self-serve analytics while shaping data models for reporting and decisioning across WW Advertising.

Qualifications

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

Responsibilities

• Design, implement, and support data warehouse / data lake infrastructure using AWS big data stack, Python, Redshift.
• Develop and manage ETLs to source data from various data lakes and create unified data model for analytics and reporting.
• Empower technical and non-technical, internal customers to drive their own analytics and reporting (self-serve reporting) and support ad-hoc reporting when needed.
• Develop deep understanding of vast data sources and know exactly how, when, and which data to use to solve particular business problems.
• Manage numerous requests concurrently and strategically, prioritizing when necessary collaborate across teams to deliver results.
• Mentor other engineers, influence positively team culture, and help grow the team.

Skills

SQL

Data modeling

ETL pipelines

Big data infrastructure design

Mentoring

Tools

AWS Redshift

AWS S3

AWS Glue

AWS EMR

AWS Kinesis

AWS Firehose

AWS Lambda

IAM roles and permissions

Job description

Data Engineer II, Sales Data Services (SDS)

Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital display advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers reach Amazon customers on Amazon.com, across our other owned and operated sites, on other high-quality sites across the web, and on millions of Kindles, tablets, and mobile devices. We start with the customer and work backwards in everything we do, including advertising. If you’re interested in joining a rapidly growing team working to build a unique, world-class advertising group with a relentless focus on the customer, you’ve come to the right place.

SDS is part of the Sales Intelligence, Technology, & Enablement organization (SITE). We are a big-data focused engineering team that provides unique, pan-Amazon datasets consolidating advertiser, seller, and vendor KPIs, exposed via data warehousing , fast APIs and agentic soutions. Our data platform is designed to serve Sales teams across WW Advertising orgs for various applications including business processes, ML, account management, marketing, and decisioning systems.

Key job responsibilities

• Design, implement, and support data warehouse / data lake infrastructure using AWS big data stack, Python, Redshift.
• Develop and manage ETLs to source data from various data lakes and create unified data model for analytics and reporting.
• Empower technical and non-technical, internal customers to drive their own analytics and reporting (self-serve reporting) and support ad-hoc reporting when needed.
• Develop deep understanding of vast data sources and know exactly how, when, and which data to use to solve particular business problems.
• Manage numerous requests concurrently and strategically, prioritizing when necessary collaborate across teams to deliver results.
• Mentor other engineers, influence positively team culture, and help grow the team.

Basic Qualifications

• 3+ years of data engineering experience
• 4+ years of SQL experience
• Experience with data modeling, warehousing and building ETL pipelines

Preferred Qualifications

• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

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