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Real job — pulled straight from Amazon’s careers page · Verified August 15, 2026 · No reposts.
Job description
Amazon is hiring a Data Engineer — a full-time, based in Hyderabad, Telangana role. Apply directly on Amazon's careers page below.
- Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or related fields
- 1+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with one or more scripting language (e.g., Python, KornShell, Scala)
- Experience with database, data warehouse or data lake solutions
- 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 with data visualization software (e.g., AWS QuickSight or Tableau) or open-source project
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Every day, millions of packages move through Amazon's fulfillment network, powered by robotics, machine learning, and massive data systems. The Amazon Fulfillment Technologies (AFT) Data Engineering team builds and operates the analytical data infrastructure behind this network. Our pipelines process billions of transactions daily from robotic fulfillment centers, powering productivity measurement, capacity planning, and operational decision-making tools used by leaders across 1,000+ sites globally.
As a Data Engineer on this team, you will build and maintain data pipelines that transform raw operational signals (robotic pick/stow events, labor activity, shipment tracking) into reliable analytical datasets. You will work across Amazon's data stack including Redshift, Spark/EMR, and Amazon's internal data catalog (Andes) to deliver data that drives real-time and weekly business decisions at scale.
Key job responsibilities
* Build and maintain ETL/ELT pipelines that process fulfillment center operational data
* Write and optimize SQL for complex analytical transformations in Redshift and Spark
* Support data quality monitoring and respond to data pipeline incidents
* Implement data models following established patterns (star schema, additive models)
* Collaborate with Business Intelligence Engineers and scientists to understand data requirements
* Document data pipelines, schemas, and lineage for team knowledge sharing
* Support existing data infrastructure and assist with migrations to newer platforms
A day in the life
You will start your day checking pipeline health dashboards and addressing any overnight failures. You might spend the morning writing SQL to transform raw robotics data into productivity metrics, then pair with a senior engineer in the afternoon to design a new data model. You will participate in code reviews, contribute to on-call rotations, and work with business stakeholders to understand what questions they need data to answer.
About the team
Amazon Fulfillment Technologies (AFT) powers Amazon's global fulfillment network. We invent and deliver software, hardware, and data science solutions that orchestrate processes, robots, machines, and people. We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it.
The AFT Data Engineering team specifically owns the data pipelines and analytical tables that measure fulfillment center performance. Our data powers leadership decision-making from individual site managers to VP-level business reviews.
- 1+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with one or more scripting language (e.g., Python, KornShell, Scala)
- Experience with database, data warehouse or data lake solutions
- 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 with data visualization software (e.g., AWS QuickSight or Tableau) or open-source project
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Every day, millions of packages move through Amazon's fulfillment network, powered by robotics, machine learning, and massive data systems. The Amazon Fulfillment Technologies (AFT) Data Engineering team builds and operates the analytical data infrastructure behind this network. Our pipelines process billions of transactions daily from robotic fulfillment centers, powering productivity measurement, capacity planning, and operational decision-making tools used by leaders across 1,000+ sites globally.
As a Data Engineer on this team, you will build and maintain data pipelines that transform raw operational signals (robotic pick/stow events, labor activity, shipment tracking) into reliable analytical datasets. You will work across Amazon's data stack including Redshift, Spark/EMR, and Amazon's internal data catalog (Andes) to deliver data that drives real-time and weekly business decisions at scale.
Key job responsibilities
* Build and maintain ETL/ELT pipelines that process fulfillment center operational data
* Write and optimize SQL for complex analytical transformations in Redshift and Spark
* Support data quality monitoring and respond to data pipeline incidents
* Implement data models following established patterns (star schema, additive models)
* Collaborate with Business Intelligence Engineers and scientists to understand data requirements
* Document data pipelines, schemas, and lineage for team knowledge sharing
* Support existing data infrastructure and assist with migrations to newer platforms
A day in the life
You will start your day checking pipeline health dashboards and addressing any overnight failures. You might spend the morning writing SQL to transform raw robotics data into productivity metrics, then pair with a senior engineer in the afternoon to design a new data model. You will participate in code reviews, contribute to on-call rotations, and work with business stakeholders to understand what questions they need data to answer.
About the team
Amazon Fulfillment Technologies (AFT) powers Amazon's global fulfillment network. We invent and deliver software, hardware, and data science solutions that orchestrate processes, robots, machines, and people. We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it.
The AFT Data Engineering team specifically owns the data pipelines and analytical tables that measure fulfillment center performance. Our data powers leadership decision-making from individual site managers to VP-level business reviews.
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Frequently asked questions
What skills are required for Data Engineer at Amazon?
The required skills for Data Engineer at Amazon include: Data Warehousing, ETL, Python, Scala, SQL, Redshift, S3, EMR, Kinesis, Lambda, IAM, Hadoop, Hive, Spark, Tableau.
What is the seniority level for Data Engineer at Amazon?
Data Engineer at Amazon is a Entry level position.
How do I apply for Data Engineer at Amazon?
You can view the full description and apply for Data Engineer at Amazon on EchoJobs: https://echojobs.io/job/amazon-data-engineer-aft-bi-content-hz15m.