Opportunities in United States

Full Job Description

Are you passionate about building data platforms that empower thousands of users to discover, trust, and act on data? Do you thrive in fast-paced environments where you can design scalable systems, automate data workflows, and drive innovation through modern cloud technologies? If you enjoy solving complex data challenges and delivering solutions that have direct business impact, then the Worldwide Operations Finance Standardization & Automation (S&A) team has an exciting opportunity for you!

We are seeking a customer-centric Data Engineer to help build and scale our unified data management and discovery platform — enabling global Finance teams to find the right data faster, ensure data quality, and make confident, data-driven business decisions. You will work with one of the world's largest and most complex data environments, building solutions that serve thousands of customers across multiple domains.

As a Data Engineer in WW Ops S&A, you will design, implement, and maintain scalable data infrastructure, ETL pipelines, and platform services that power enterprise-scale data discovery and analytics. You will build solutions to integrate with multiple heterogeneous data sources, develop metadata management frameworks, and create self-service capabilities that accelerate time-to-insight. You should have strong technical skills in Python, SQL, and AWS services, along with excellent communication skills to collaborate with business owners, Finance teams, and engineering partners to translate requirements into reliable, scalable solutions.

Key job responsibilities

• Design, build, and maintain scalable data pipelines and ETL workflows using Python, SQL, and AWS services (S3, Glue, Redshift, Lambda, EMR, MWAA) to support enterprise-scale data platforms
• Develop and optimize data models, metadata management frameworks, and catalog systems that enable fast, reliable data discovery for thousands of internal customers
• Build and maintain microservices and APIs (API Gateway, Lambda) that power platform features including search, data ingestion, and cross-service integrations
• Implement data quality frameworks, monitoring, and alerting to ensure high data reliability, freshness, and compliance with governance standards
• Automate data onboarding workflows and self-service capabilities to reduce manual effort and accelerate time-to-insight for data consumers and producers
• Collaborate 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 the data discovery and analytics experience

About the team We are part of the Worldwide Operations Finance Standardization & Automation (S&A) organization, building a unified data management and discovery platform serving global Finance teams. Our platform combines a dataset catalog, metric catalog, AI assistant, and interactive query experience enabling thousands of customers to find and act on data faster. We are rapidly scaling to support 10+ domains and data producer teams. Our tech stack includes AWS services (DataZone, OpenSearch, API Gateway, Lambda), microservices architecture, and modern frontend frameworks.

Basic Qualifications

• 3+ years of data engineering experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using each of the following: ETL (Extract, Transform, Load)/ELT (Extract, Load, Transform) processes experience
• Bachelor's degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field
• 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)
• Experience with Apache Spark / Elastic Map Reduce

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Bellevue - 132,100.00 - 178,800.00 USD annually

3+ years of data engineering experience 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience 1+ years of developing and operating large-scale data structures for business intelligence analytics using Oracle experience 1+ years of developing and operating large-scale data structures for business intelligence analytics using each of the following: ETL (Extract, Transform, Load)/ELT (Extract, Load, Transform) processes experience Bachelor's degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field Experience with data modeling, warehousing and building ETL pipelines