Principal Pricing Data Engineer

Responsibilities

• Design and build scalable, reliable data pipelines that ingest, validate, transform, and persist pricing-relevant data, including: Transactional sales data (orders, invoices, contracts), Price lists, discounts, rebates, and surcharges, Cost, margin, and profitability data
• Develop and maintain pricing-specific data models, including: Price waterfall, Customer and product segmentation hierarchies, Realized price and margin analytics
• Define and implement the end-to-end pricing data architecture, ensuring integration across systems such as ERP, CRM, and CPQ.
• Establish scalable frameworks to support global pricing governance and standardization across divisions and regions.
• Contribute to and influence data platform design for analytics, machine learning, and Agentic AI workloads, with a focus on pricing use cases.
• Build high-performance data pipelines capable of supporting: Large-scale transactional datasets, Near real-time pricing insights and monitoring
• Implement and maintain data quality checks, validation logic, and monitoring dashboards to ensure pricing data integrity and auditability.
• Optimize data pipelines for performance, cost efficiency, and scalability in cloud environments.
• Partner closely with Global Pricing and Commercial teams to translate business problems into scalable data solutions.
• Enable advanced pricing analytics, including: Price realization and leakage analysis, Discount and rebate effectiveness, Customer/product elasticity modeling (in collaboration with data science)
• Support development of pricing dashboards, KPIs, and reporting frameworks used by senior leadership.
• Develop production-grade Python code using strong OOP and functional programming practices.
• Follow and promote sound engineering practices, including modular design, testing, readability, and maintainability.
• Participate actively in code reviews, automated testing, and source control workflows.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or a related field, plus 8+ years of relevant industry experience, or equivalent practical experience.
• Advanced proficiency in Python and SQL, with a strong focus on data engineering use cases.
• Solid understanding of source control, collaborative development workflows, and production support.
• Strong experience working with commercial and pricing-related data (e.g., sales transactions, pricing, margins, rebates).
• Experience mentoring peers and contributing to technical best practices within a team environment.
• Strong communication skills and the ability to work effectively with both technical and non-technical partners.
• Demonstrated drive, curiosity, humility, and ability to learn.