OverviewThe Principal Data Engineer will lead the architecture, development, and optimization of scalable data solutions that power insights across Commercial Excellence, and enterprise process initiatives. This role focuses on end-to-end data engineering - from ingestion and modeling through automation and governance - with responsibility for enabling high-quality analytics. The engineer will own the delivery of analytics data assets and also deliver select production-grade report development in Power BI, ensuring that strategic dashboards are reliable, performant, and widely adopted.
Role ImpactThis role will shape the Commercial Excellence data and reporting foundation - enabling trusted, fast, and actionable insights, accelerating enterprise transformations (e.g., S/4HANA, Customer Master redesign), and elevating analytics maturity across Waters.
This is a Hybrid role based out of Milford, MA 3 days a week (Tuesday to Thursday)Responsibilities1) Data Engineering & Architecture - Design, develop, and maintain scalable data pipelines across SAP S/4 Salesforce, Marketo, Adobe Analytics, and other core enterprise systems.
- Architect and implement data models in Databricks, Synapse or similar platforms.
- Build ingestion frameworks, transformation logic, and orchestration workflows (e.g., Azure Data Factory, Databricks Jobs).
- Implement data quality, validation, and monitoring frameworks; codify tests and SLAs for critical datasets.
- Lead development of enterprise-grade semantic models and reusable data assets supporting Sales, Marketing and Finance
- Partner with IT, Master Data, and Process Excellence teams to align data structures with evolving enterprise process designs (Lead to Cash, Demand Gen, Customer Master, Pricing).
2) Power BI Reporting - Engineer performant Power BI datasets, dataflows, and semantic models; define and maintain measures (DAX), calculation logic, and row-level security where required.
- Design and build prioritized enterprise dashboards and paginated reports in Power BI, partnering with business stakeholders on UX, KPIs, and adoption.
- Establish standards for dataset refresh, parameterization, gateway configuration, and workspace governance; resolve performance bottlenecks (model size, query folding, DAX).
- Enable self-service by publishing certified datasets and patterns; review community reports for conformance and reliability.
3) Process Intelligence, Automation & Cross-Functional Collaboration- Deliver integrated data models for process mining and operational analytics (e.g., Lead12Opportunity12Order12Invoice).
- Drive alignment on data definitions, lineage, ownership, and governance across stakeholders; document lineage and critical data elements.
- Mentor engineers and analysts; champion code reviews, version control, and deployment automation.
QualificationsRequired Qualifications- 7+ years in data engineering, data architecture, or analytics engineering roles.
- Expert-level SQL and Python with a strong understanding of data warehousing principles and dimensional modeling.
- Hands-on with Databricks/Spark (PySpark), and/or Azure Synapse; experience orchestrating with ADF or equivalent.
- Proven experience engineering data for Power BI and developing production dashboards (DAX, Power Query, dataflows).
- Experience with SAP, Salesforce, Marketo, or other enterprise operational systems.
- Strong grasp of data quality, lineage, governance frameworks, and master data concepts (customer, product, pricing).
- Ability to partner effectively with technical and business stakeholders in a global matrixed environment.
Preferred Qualifications- Experience in Commercial Excellence, Revenue Operations, Sales Operations, or Finance
- Familiarity with process mining (Celonis) and event-based data models.
- DevOps for data: Git, CI/CD, environment promotion, automated testing.
- Experience with privacy/compliance and secure data design (RLS, PII handling).
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