Data Engineer

Job Description A large life sciences companyh is seeking a mid-level Data Engineer to work remotely near shore or off shore. THis person will be responsible for supporting the development, enhancement, and maintenance of data products that drive planning, logistics, and operational decision-making for their Clinical Supply Chain organization. This role requires a well-rounded engineer who can build and maintain data pipelines, contribute to data modeling efforts, ensure data reliability, and work independently within an agile environment. The ideal candidate has strong hands-on experience with dbt, SQL, and data engineering, along with the ability to transform raw data into curated datasets that support analytics, forecasting, and business insights. Key Responsibilities Design, build, and maintain scalable data pipelines and data transformation processes using dbt. Develop and optimize data models to support reporting, forecasting, and operational decision-making. Integrate new data sources into existing platforms and data products. Perform data quality validation, testing, and monitoring to ensure reliability and accuracy of business-critical data. Create and maintain dbt and SQL-based tests, alerts, and validation processes. Support a mix of: New feature development Production support and bug fixes Ad hoc business requests Collaborate with stakeholders to understand business requirements and translate them into technical solutions. Document development work, testing results, and technical specifications.

Participate in Agile development processes, including Jira-based workflow management. Skills and Requirements 3-8 years of experience as a Data Engineer. Strong hands-on experience with dbt (required). Advanced SQL skills. Experience building and maintaining data pipelines and ETL/ELT processes. Experience with data modeling and database design. Ability to independently test, validate, and troubleshoot code. Experience working in Agile environments and using Jira. Strong documentation and communication skills. Ability to perform data quality checks and ensure data reliability. Python development experience. Experience with Airflow. Snowflake experience. Experience working within Data Cove environments. Experience supporting both development and production environments.