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# Senior Data Engineer

- **Company:** Charles River Laboratories International, Inc.
- **Location:** Wilmington, MA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $100,000.0 - $185,000.0
- **Contract:** Permanent contract
- **Skills:** Business Analytics Applications, Microsoft Azure, Big Data, Computer Programming, Computer Engineering, Data Integration, Extract Transform Load (ETL), Data Systems, Data Warehousing, Relational Databases, Hadoop Distributed File System, Apache Hive, SQL Azure, Performance Tuning, Azure Data Lake, Sqoop, Transact-SQL, Enterprise Data Management, Azure Data Factory, Apache Spark, Information Technology, Data Analytics, Performance Monitor, Cosmos DB, Data Pipelines, Serverless Computing, Databricks
- **Published:** May 19, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=dfbc6125913efbc5

## About the Role

Bachelor's degree, in Computer Engineering, Computer Science, Electronic Engineering, or related field, or foreign degree equivalent. Plus, seven (7) years of experience in ETL design, performance optimization, and implementation in a multi-dimensional Data Warehousing environment.

The experience (which may be gained concurrently) must also include each of the following:

 * 7 years of advanced SQL Programming: T-SQL;
 * 5 years of experience in designing and implementing Enterprise Data & Analytics solutions, focusing on architecture and strategy development to drive data-driven business decisions;
 * 3 years of hands-on experience with data-heavy and analytics applications, utilizing relational databases, data warehousing, and big data technologies such as HDFS, Hive, Sqoop, Spark, and Python for data processing and analysis; and
 * 2 years of experience with Azure cloud technologies, including Azure Data Factory, Azure Data Lake Gen2, Azure Databricks, Blob Storage, Azure SQL Database, Azure Functions, and Cosmos DB, enabling scalable and efficient data pipelines and solutions.

## Description

* Data Architecture Design and Optimization: Designing, implementing, and optimizing data architecture on Azure, including databases, data lakes, and data warehouses.
 * Azure Data Services Implementation: Implementing and managing Azure data services such as Azure SQL Database , Azure Data Lake Storage, and others.
 * ETL (Extract, Transform, Load) Pipeline Development: Building and maintaining ETL pipelines to move and transform data from various sources to target destinations in Azure.
 * Data Integration and Transformation: Integrating data from diverse sources and transforming it into a unified format for analysis.
 * Performance Monitoring and Optimization: Monitoring the performance of data systems and optimizing queries, storage, and processing for efficiency.
 * Collaboration with Cross-functional Teams: Collaborating with data scientists, analysts, and other teams to understand their data requirements and provide necessary support.


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