Amazon is hiring a customer-focused Data Engineer for the Worldwide Operations Finance Standardization & Automation (S&A) organization. The position is focused on building and scaling a unified data management and discovery platform that supports global Finance teams.
Key Responsibilities
- Design, build, and maintain scalable data pipelines and ETL workflows using Python, SQL, and AWS services including S3, Glue, Redshift, Lambda, EMR, and MWAA for enterprise-scale data platforms.
- Develop and optimize data models along with metadata management frameworks and catalog systems to enable reliable, fast data discovery for thousands of internal customers.
- Build and maintain microservices and APIs using API Gateway and Lambda to support platform features such as search, data ingestion, and cross-service integrations.
- Implement data quality frameworks, monitoring, and alerting to support high data reliability, freshness, and compliance with governance standards.
- Automate data onboarding workflows and self-service capabilities to reduce manual effort and improve time-to-insight for both data consumers and producers.
- Partner with cross-functional teams, including product managers, BI engineers, and business stakeholders, to translate business requirements into scalable technical solutions.
- Participate in system design, code reviews, and operational excellence practices, including incident response, root cause analysis, and continuous improvement.
- Contribute to GenAI-powered features and AI-driven workflows that enhance data discovery and analytics experiences.
Required Qualifications
- 3+ years of data engineering experience.
- 1+ year developing and operating large-scale data structures for business intelligence analytics using OLAP technologies.
- 1+ year developing and operating large-scale data structures for business intelligence analytics using SQL.
- 1+ year developing and operating large-scale data structures for business intelligence analytics using Oracle.
- 1+ year developing and operating large-scale data structures for business intelligence analytics using ETL (Extract, Transform, Load) and/or ELT (Extract, Load, Transform) processes.
- Bachelor’s degree (or foreign equivalent) in Computer Science, Engineering, Information Systems, Mathematics, or a related field.
- Experience with data modeling, data warehousing, and building ETL pipelines.
Technologies
Python, SQL, AWS services (S3, Glue, Redshift, Lambda, EMR, MWAA), API Gateway, ETL, ELT, Oracle, OLAP technologies, DataZone, OpenSearch, Kinesis, FireHose, IAM roles and permissions, non-relational databases/data stores (object storage, document or key-value stores, graph databases, column-family databases), Apache Spark, and Elastic Map Reduce.
Team and Platform Overview
The role is part of the Worldwide Operations Finance Standardization & Automation (S&A) organization. The team builds a unified data management and discovery platform for global Finance teams, combining a dataset catalog, metric catalog, AI assistant, and interactive query experience. The platform is scaling to support 10+ domains and data producer teams, with a stack that includes AWS services such as DataZone, OpenSearch, API Gateway, and Lambda, along with a microservices architecture and modern frontend frameworks.
Preferred Qualifications
- Experience with AWS technologies such as 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).
- Experience with Apache Spark / Elastic Map Reduce.
Benefits
- Health insurance (medical, dental, vision, prescription)
- Basic Life & AD&D insurance and option for Supplemental life plans
- EAP
- Mental Health Support
- Medical Advice Line
- Flexible Spending Accounts
- Adoption and Surrogacy Reimbursement coverage
- 401(k) matching
- Paid time off
- Parental leave
Role Details
Location: Bellevue, WA (onsite)
Salary: USD 132,100 - 178,800 per year
Minimum Experience: 3 years
