Data Engineer Analyst

Requisition ID: 72661  About Whirlpool Corporation   Whirlpool Corporation (NYSE: WHR) is a leading home appliance company, in constant pursuit of improving life at home. As the only major U.S.-based manufacturer of kitchen and laundry appliances, the company is driving meaningful innovation to meet the evolving needs of consumers through its iconic brand portfolio, including Whirlpool , KitchenAid , JennAir, Maytag , Amana, Brastemp , Consul , and InSinkErator . In 2025, the company reported approximately $16 billion in annual net sales - close to 90% of which were in the Americas - 41,000 employees, and 35 manufacturing and technology research centers. Additional information about the company can be found at   WhirlpoolCorp.com .    The team you will be a part of 
 The Global Information Technology team plays a strategic role in driving technology and digital transformation across the company. The Data and AI team is responsible for design, deliver, and evolve technology solutions to improve data usage and drive long-term business results. This role in summary 
 We are seeking a skilled Data Engineer to design, build, and maintain the data infrastructure that powers our analytics, products, and decision-making processes. You will be responsible for developing scalable data pipelines, optimizing data workflows, and ensuring high-quality, accessible data across the organization. This role requires strong technical expertise, problem-solving skills, and the ability to collaborate with cross-functional teams including data scientists, analysts, and software engineers. Your responsibilities will include 
 Builds Data Pipelines prioritized by D&A (with support of DE lead and Data product owner); Performs and documents Unit Tests for Data Pipelines; Supports Data Product Owners (BI Teams and Data Science Team) on UAT Tests; Coordinates Data Pipeline deployment (creates pull Request, requests Business approval, creates cutover plan, loads historical data, coordinates deployment with vendors and requests schedules); Follows Solution Architecture, Data Architecture and Data Governance policies; Documents developed Data Pipelines following Project documentation & Product documentation (KT); Trains Data Sutain Team on deployed data pipelines (KT); Minimum requirements 
 Hands-on experience building and maintaining batch and streaming data pipelines using Dataflow, Pub/Sub, and Cloud Storage , following established production patterns. Strong proficiency in BigQuery , including partitioning, clustering, basic performance optimization, and cost-aware design under guidance. Experience with workflow orchestration using Cloud Composer (Airflow) , including task dependencies, retries, and failure handling. Proficiency in Python for data processing, with experience writing unit tests using frameworks such as pytest and applying data quality validation checks. Good understanding of analytical data modeling , including Star Schema concepts and Medallion Architecture (Bronze/Silver/Gold) . Solid software engineering fundamentals, including Git-based workflows , participation in code reviews , and basic experience with Docker and CI/CD pipelines (e.g., Cloud Build). Working knowledge of GCP fundamentals , including IAM , service accounts, and basic VPC and network security Preferred skills and experiences 
 Exposure to enterprise cloud platforms beyond GCP (e.g., AWS or Azure ) or hybrid data environments. Familiarity with reference architectures , data product concepts , and domain-oriented data platforms. Basic knowledge of SAP systems (ECC, BW, or S/4) and enterprise source system integration. Exposure to enterprise integration tools such as Informatica or WSO2 (hands-on or project-level). Awareness of data security, compliance, and governance practices , including access controls and data sensitivity. Experience participating in knowledge transfer (KT) activities and supporting operational or sustain teams. Strong