Principal Data Engineer; Service

Overview

Come help us transform Waters Corporation. Transformation at Waters Corporation is driving the next phase of enterprise evolution. Our mission is to accelerate integration, execution, and value capture while transforming the capabilities that power our business.

As part of our transformation journey, we are building the data foundations required for both integration and advancing technologies, including Agentic AI. These capabilities support data-driven decisions across the enterprise, enabling better insights, improved processes, and more efficient operations.

This is a unique opportunity to join a team at the center of Waters' transformation, working on high-impact initiatives that shape the future of the enterprise.

As a Principal Data Engineer (Service), you will be a senior technical contributor who partners closely with the Service Excellence team, data and analytics teams, and service business leaders across four commercial divisions representing $1.7B in service revenue. You will bring deep technical expertise in service business data domains, operate with a high degree of independence, and contribute to the design and delivery of scalable data platforms that enable strategic decision-making for revenue growth, margin expansion, and operational excellence initiatives targeting $200M+ in EBIT improvement.

Role Overview

The Principal Data Engineer (Service) designs, builds, and enhances robust data platforms and pipelines that integrate service delivery, financial, operational, and workforce data to support strategic planning, business case development, and performance monitoring. This role is primarily hands‑on, with opportunities to contribute to platform design, data integration architecture, and cross‑team collaboration. You will be a key problem solver for complex service data challenges and a trusted partner to both technical and business stakeholders driving service transformation.

Data Engineering

• Design and build scalable, reliable data platforms that integrate service delivery data (work orders, cases, products, geography), service team member data (roles, locations, workloads), service revenue and cost data, and proforma P&L information to enable strategic decision-making.
• Develop and maintain data pipelines that ingest, validate, transform, and persist data from enterprise systems including Salesforce, Service Max, SAP ERP, Ring Central, and Genesys, ensuring data quality and reliability.
• Contribute to data platform design for analytics, business case modeling, capacity optimization, and operational monitoring workloads, with a focus on performance, reliability, and maintainability.
• Implement and maintain data quality checks, validation logic, and monitoring dashboards to ensure data health and trust across service business domains.

Software Engineering

• 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.

Analytics & Business Enablement

• Partner with Service Excellence leaders, Finance Business Partners, and Data Scientists to ensure data is model‑ready, reproducible, and well understood for business case development, financial planning, and performance tracking.
• Support analytical workflows that enable proforma P&L modeling, capacity optimization, margin analysis, and value realization tracking across service transformation initiatives.
• Translate service business requirements into scalable data solutions that support revenue growth, operational excellence, and integration objectives.

Required 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.
• Proven experience building and operating end-to-end data pipelines (ETL/ELT) in modern data environments.
• Experience integrating and enhancing data from enterprise systems…