Principal Data Engineer

Responsibilities

• Serve as a hands‑on technical leader responsible for designing, building, and optimizing Cambridge's modern data platform.
• Help define data architecture standards, lead engineering efforts, mentor team members, and drive scalable data solutions.
• Design, develop, and maintain scalable data pipelines supporting enterprise reporting, analytics, and business applications.
• Build and optimize ETL/ELT solutions using modern cloud‑based technologies.
• Design and implement data integration solutions utilizing Azure Data Factory (ADF), Azure Functions, and other Azure services.
• Develop and maintain datasets within Snowflake and Azure Data Lake Storage (ADLS) environments.
• Lead data platform architecture initiatives, including data modeling, ingestion, transformation, storage, and consumption patterns.
• Drive performance tuning and cost optimization efforts across cloud data platforms and processing workloads.
• Design secure, reliable data movement solutions using batch and streaming integration patterns.
• Establish engineering best practices, code reviews, and architectural standards.
• Mentor data engineers and provide technical leadership across projects.
• Partner with analytics, product, and business stakeholders to deliver scalable, high‑quality data solutions.

• 8+ years of experience in data engineering, data architecture, or related technical roles.
• Strong hands‑on experience with:
  • Snowflake (SQL)
  • Azure Data Factory (ADF)
  • Azure Data Lake Storage (ADLS)
  • Azure Functions
  • Data Pipeline Development
  • ETL / ELT Design and Implementation
  • Performance Tuning
  • Cloud Cost Optimization
  • Python
• Strong SQL development and data modeling expertise.
• Experience designing scalable data integration and analytics solutions in Azure.
• Knowledge of modern data architecture patterns and best practices.