About The Position

The AWS Sales Marketing Global Services Ops (SMGS Ops) Revenue team publishes mission-critical Sales Revenue data product including, Unified Estimated Revenue, GAAP Sales Revenue, Quota Sales Retirement, and Planning Revenue that power strategic decision-making across AWS Finance, Accounting, Sales Operations, Segmentation Planning & Policy (S&P), Global Sales Compensation, Field Experience, and Data & Analytics teams. Our platform processes billions of metered usage and billing transactions daily, integrating data from 20+ sources including Salesforce.com to deliver accurate, timely revenue insights that drive quota setting, sales goal management, forecasting, compensation, and business intelligence. We leverage BigData technologies including Elastic Map Reduce (EMR), Spark, Redshift, and Glue and other AWS services to handle massive data volumes at scale. The Opportunity We're seeking a passionate Senior Data Engineer to architect and extend our processing framework for next-generation revenue data products. In this high-impact role, you'll: • Build scalable data pipelines that seamlessly handle exponential data growth and enable rapid development of new revenue products • Lead AI-driven automation initiatives to transform revenue processing—from data acquisition and validation to publishing and insights generation—into intelligent, systematic workflows • Architect solutions that enhance data quality, reduce processing latency, and deliver actionable insights to stakeholders across the organization This role places you at the forefront of innovation, combining big data engineering with AI/ML to revolutionize how AWS processes and reports revenue at global scale.

Requirements

  • 5+ years of data engineering experience
  • Experience with data modeling, warehousing and building ETL pipelines
  • Experience with SQL
  • Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
  • Experience mentoring team members on best practices

Nice To Haves

  • Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
  • Experience operating large data warehouses

Responsibilities

  • Drive technical excellence and organizational growth: Evolve the Revenue technology stack to support AWS's rapid expansion while maintaining compliance with security policies, architectural standards, and operational best practices
  • Deliver high-impact data solutions: Design and build end-to-end pipelines that transform raw data from diverse upstream sources into actionable business insights powering quota management, forecasting, and compensation decisions
  • Innovate through automation: Develop frameworks, tools, and AI-driven solutions that eliminate manual processes, reduce operational overhead, and accelerate time-to-insight for Revenue customers
  • Design scalable data models: Create and maintain dimensional models and data structures that enable self-service analytics and support evolving reporting requirements across Finance, Sales Operations, and Analytics teams
  • Lead and mentor engineering talent: Build and guide a high-performing team of Data Engineers to deliver cross-functional solutions, foster technical growth, and establish engineering excellence standards
  • Architect and optimize Revenue data infrastructure: Ensure enterprise-grade security, cost efficiency, and scalability while processing billions of daily transactions across 20+ data sources
  • Partner across the organization: Collaborate with product managers, stakeholders, and customers to translate business requirements into technical solutions and influence the Revenue product roadmap

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
© 2024 Teal Labs, Inc
Privacy PolicyTerms of Service