Data Engineer I, Inventory Health Tech (SCOT)
ADCI HYD 13 SEZ · Hyderabad, India · Data Engineering
Full-time
About the role
The Inventory Health team is looking for a Data Engineer. The team manages the inventory health for Amazon's emerging marketplaces - India, Brazil, Japan, MENA, and Mexico. The data engineer shall help us in building data pipelines, launching features for emerging retail stores, and create analytics infrastructure that feed supply chain systems. The work directly influences in-stock rates, excess inventory, and delivery speed for million of items. The role sits at the intersection of software engineers and applied scientists, and defines how supply chain signals are captured, transformed, and served across countries with very different fulfillment structures.
Key job responsibilities
1. Build, own and manage large-scale data pipelines that ingest, transform, and serve supply chain signals for inventory optimization
2. Build features and data applications for experimentation, ML model training, and production systems across multiple marketplaces.
3. Work with SDEs & Science teams to define data contracts, validate feature quality, and iterate on data representations that feed downstream models.
4. Build monitoring, alerting, and self-healing mechanisms for pipelines. Broken data means wrong inventory decisions at scale.
5. Be Curious to understand end to end systems beyond typical data engineering boundaries.
A day in the life
No two days look the same. Some days you are debugging a broken pipeline because an upstream team changed a schema without notice. Other days you are designing a new feature table for an upcoming ML model. While, also explaining to non-technical audience on what your data says. The work swings between deliberate building and reactive fixing of broken pipelines - you need to be comfortable with both. Beyond the work itself, we value work-life balance. The team is approachable, supportive, and nobody expects you to figure things out alone.
About the team
We are the Calibrated Inventory team under SCOT (Supply Chain Optimization Technologies). The org is responsible for deciding what Amazon buys, where it places the inventory, and how it ships. Our team specifically focuses on inventory health - deciding when Amazon holds too much, or too little, or holds on to a wrong stuff for too long - and rectifies it to achieve maximum value for our customers
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with data visualization software (e.g., AWS QuickSight or Tableau) or open-source project
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
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.
Key job responsibilities
1. Build, own and manage large-scale data pipelines that ingest, transform, and serve supply chain signals for inventory optimization
2. Build features and data applications for experimentation, ML model training, and production systems across multiple marketplaces.
3. Work with SDEs & Science teams to define data contracts, validate feature quality, and iterate on data representations that feed downstream models.
4. Build monitoring, alerting, and self-healing mechanisms for pipelines. Broken data means wrong inventory decisions at scale.
5. Be Curious to understand end to end systems beyond typical data engineering boundaries.
A day in the life
No two days look the same. Some days you are debugging a broken pipeline because an upstream team changed a schema without notice. Other days you are designing a new feature table for an upcoming ML model. While, also explaining to non-technical audience on what your data says. The work swings between deliberate building and reactive fixing of broken pipelines - you need to be comfortable with both. Beyond the work itself, we value work-life balance. The team is approachable, supportive, and nobody expects you to figure things out alone.
About the team
We are the Calibrated Inventory team under SCOT (Supply Chain Optimization Technologies). The org is responsible for deciding what Amazon buys, where it places the inventory, and how it ships. Our team specifically focuses on inventory health - deciding when Amazon holds too much, or too little, or holds on to a wrong stuff for too long - and rectifies it to achieve maximum value for our customers
Basic qualifications
- 1+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines
- Experience with data visualization software (e.g., AWS QuickSight or Tableau) or open-source project
Preferred qualifications
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
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.