Principal Data Engineer

Overview

Come help us transform Waters Corporation (NYSE: WAT) 

The Transformation team 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 our enterprise. As a Principal Data Engineer, you will be a senior technical contributor who partners closely with data, analytics, and product teams. You will bring deep technical expertise, operate with a high degree of independence, and contribute to the design and delivery of scalable data solutions while mentoring others and influencing best practices. 

Responsibilities

The Principal Data Engineer designs, builds, and enhances robust data pipelines and platforms that support analytics, machine learning, and operational monitoring. This role is primarily hands‑on, with opportunities to contribute to system design, code quality, and cross‑team collaboration. You will be a key problem solver for complex data challenges and a trusted partner to both technical and business stakeholders. 

Key Responsibilities 

Data Engineering 

• Design and build scalable, reliable data pipelines that ingest, validate, transform, and persist structured and semi‑structured data, including large data frames and matrices.
• Contribute to data platform and pipeline design for analytics, machine learning, and Agentic AI 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. 

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 & ML Enablement 

• Partner with Data Scientists and Analysts to ensure data is model‑ready, reproducible, and well understood. 
• Support analytical and machine learning workflows from raw data ingestion through downstream outputs and monitoring. 

 

Qualifications

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. 
• Solid understanding of source control, collaborative development workflows, and production support. 
• 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. 

Nice‑to‑Have / Plus Qualifications 

• Familiarity with process mining platforms such as Celonis, including working with event‑based data and enabling transparency into end‑to‑end business processes. 
• Strong business domain knowledge and experience working with enterprise systems such as SAP (e.g., supply chain data, orders, revenue recognition, pricing), Salesforce (commercial or service processes), with the ability to translate business processes into scalable data solutions.                                                                                         #LI-Hybrid