Product Data Engineer – Service Sales & Performance -- Hybrid -- Only W2

Job Title: Product Data Engineer – Service Sales & Performance
Location: Lisle, IL – Hybrid
Interview Process: Mandatory Face-to-Face Interview
Job Summary
We are seeking an experienced Product Data Engineer to support Service Sales & Performance initiatives. The ideal candidate will have strong expertise in data engineering, business analysis, data modeling, and modern data platforms.
This role involves building and maintaining reliable data pipelines, developing data models, supporting operational reporting, and ensuring data quality across service-related business processes. The candidate will work closely with business and technical teams to translate business requirements into scalable data solutions.
Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Python, SQL, Databricks, and Azure Data Services.
• Build and optimize data models and operational data products to support business reporting and decision-making.
• Work with modern Lakehouse architectures and enterprise data platforms.
• Analyze service-related business processes, including product configuration, pricing, order management, contracts, subscriptions, entitlements, maintenance, and warranty operations.
• Implement data quality checks, reconciliation processes, monitoring, and exception management.
• Integrate data from APIs, batch processes, and change data capture (CDC) or event-driven systems.
• Ensure data lineage, testing, observability, access controls, and production reliability.
• Troubleshoot data pipeline issues and provide production support.
• Collaborate with business stakeholders to gather requirements and translate them into technical specifications and data models.
• Support data governance and master data management initiatives.

Required Skills

• Strong programming experience in Python and advanced SQL.
• Hands-on experience with Databricks and Azure Data Services.
• Knowledge of modern Lakehouse architecture.
• Experience in data engineering, data analysis, data architecture, and data modeling.
• Strong understanding of data governance and data quality management.
• Experience building and supporting production data pipelines.
• Knowledge of data reconciliation, monitoring, and exception management.
• Experience with API integrations, batch processing, and event-driven data pipelines.
• Understanding of service sales and performance processes, including pricing, order management, contracts, subscriptions, maintenance, or warranty operations.
• Ability to translate business requirements into scalable technical solutions.

Good-to-Have Skills

• Azure Data Factory (ADF).
• Palantir Foundry, including pipelines, ontology, and operational applications.
• Experience with SAP, Hadoop, DB2, or mainframe systems.
• Domain-Driven Design (DDD), Master Data Management (MDM), semantic modeling, and data governance.
• ServiceNow or other operational workflow platforms.
• Experience in automotive, commercial vehicles, industrial B2B, dealer, or distributor environments.
• Experience using statistical methods or AI techniques for anomaly detection.