Senior Data Engineer: Scalable Pipelines & ML Enablement

uscareers-waters; Milford (MA); Hybrid; USD 150,000 - 200,000; Full time

Job summary

Waters Corporation is seeking a Principal Data Engineer to design, build, and optimize scalable data pipelines supporting analytics, ML, and agentic AI workloads. This hands-on role partners with data science, analytics, and product teams to deliver robust data platforms.

You will mentor peers, promote best practices, and contribute to system design, code quality, and cross-team collaboration in a hybrid environment. A strong background in Python, SQL, and data engineering is essential.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field, plus 8+ years of relevant industry 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.

Responsibilities

• Design and build scalable, reliable data pipelines that ingest, validate, transform, and persist structured and semi-structured data.
• Contribute to data platform and pipeline design for analytics, machine learning, and Agentic AI workloads, focusing on performance and maintainability.
• Implement and maintain data quality checks, validation logic, and monitoring dashboards.

Skills

Python

SQL

End-to-end data pipelines

Mentoring

Communication

Curiosity

Education

Bachelor’s degree in Computer Science / Engineering

Tools

Celonis

SAP

Salesforce

Job description

Waters Corporation is seeking a Principal Data Engineer to design, build, and optimize scalable data pipelines supporting analytics, ML, and agentic AI workloads. This hands-on role partners with data science, analytics, and product teams to deliver robust data platforms.

You will mentor peers, promote best practices, and contribute to system design, code quality, and cross-team collaboration in a hybrid environment. A strong background in Python, SQL, and data engineering is essential.