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.
Requirements
- 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.
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