Data Engineer, Global Procurement Technology

Amazon's Global Procurement Organization manages indirect supply chain for World Wide Operations and Delivery Services. We work with massive amounts of data and leverage them for advanced applications.
We are Data Engineers to build the facilities to help enable the Global Procurement Organization to gain deep insights into all facets of indirectly supply management and apply advanced data science for automation and decision making.
You are someone who is customer focused, relentless and driven to help us build out a brand-new initiative. You will collaborate closely with product managers, developers and leaders across the org. To be successful in this role, you should have broad skills in database design, be comfortable dealing with large and complex data sets, modeling and designing a strong data warehouse and building self-service data platforms for stakeholders to utilize the data we manage.
Key job responsibilities
* Build and maintain scalable ETL/ELT data pipelines that ingest, transform, and serve procurement data across multiple systems
* Support existing data infrastructure including quality monitoring, alerting, and SLA tracking for critical business data feeds
* Implement data models and table schemas following established patterns across our data warehouse (Amazon Redshift / AWS Glue catalog)
* Work with business stakeholders and analysts to understand data requirements and deliver reliable, well-documented data products
* Contribute to data quality frameworks — write validation logic, data contracts, and anomaly detection jobs
* Participate in on-call rotations and troubleshoot pipeline failures affecting downstream procurement reporting
* Learn and apply data engineering best practices: idempotency, backfill strategies, schema evolution, and partitioning
- 1+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
- Experience with one or more scripting language (e.g., Python, KornShell)
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
- Knowledge of AWS Infrastructure
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