Job Summary
We are looking for a Product Data Engineer – Service Sales & Performance to design and support reliable data pipelines, data models, operational reporting, and data-quality solutions across enterprise systems.
The role combines Data Engineering, Business Analysis, and Domain Data Modeling and will work closely with product, engineering, data, and business teams. Key responsibilities include building operational data products, translating business processes into technical data requirements, implementing preventive data-quality controls, reconciliation and exception management, and improving production reliability.
Must-Have Skills
· Advanced SQL and Python skills with strong software-engineering practices.
· Experience with Databricks, Azure Data Services, and modern Lakehouse architectures.
· Experience with service products, configuration and pricing, order management, contracts, subscriptions, entitlements, maintenance, or warranty processes.
· Hands-on experience designing and operating production data pipelines, data models, and operational data products.
· Strong experience with data quality controls, reconciliation, monitoring, and exception management.
· Experience integrating data using APIs, batch pipelines, change data capture, or event-driven patterns.
· Strong understanding of data lineage, testing, observability, access controls, and production support.
· Ability to translate business processes and rules into technical data requirements and models.
Nice-to-Have Skills
The JD lists the following as desired skills and experience:
· Palantir Foundry, including data pipelines, ontology design, and operational applications.
· Experience with systems/platforms such as Pega, SAP, Hadoop, legacy mainframe, or DB2.
· Domain-driven design, Master Data Management, semantic modeling, and data governance.
· Experience with ServiceNow or similar workflow/support platforms for operational exceptions.
· Experience within commercial vehicle, automotive, industrial B2B, or dealer/distributor environments.
· Experience applying statistical methods or AI for anomaly detection, exception classification, or operational decision support.
· Relevant advanced degree in Computer Science, Engineering, Information Systems, Analytics, or a related discipline.
Skills
Mandatory Skills : Data Analysis, Data Architecture, Data Governance, MN_Connected Vehicle/Product, Python
Good to Have Skills : Azure Data Factory, Databricks
