​Trinity Life Sciences is a global leader in life sciences strategy and analytics. This Associate Product Support Engineer role is an entry-to-intermediate position within the Data & Analytics team. You will focus on the reliability of production systems, supporting the “always-on” nature of data-driven life sciences platforms through release management, SQL-based troubleshooting, and the adoption of DevOps practices.

• ​Location: Remote (MA, SC, RI, PA, OR, and others)
• ​Experience: 1–2 years in production support, tech ops, or DevOps.
• ​Core Tech: SQL, Python/PowerShell, Azure, ETL, Docker, Jenkins.
• ​Schedule: Includes an on-call rotation for critical after-hours issues.

​Release Management & System Monitoring

​You will play a vital role in the software delivery lifecycle by coordinating production releases and validating deployments. You will be responsible for ensuring uptime by monitoring system performance and enhancing alerting tools, identifying gaps in current coverage, and implementing new dashboards to improve observability.

​SQL & Data Operations

​Because this role sits within the Data & Analytics team, proficiency in SQL is essential. You will write and optimize queries for data validation and troubleshooting, ensuring that the ETL (Extract, Transform, Load) workflows—likely hosted in Azure—are processing data accurately and efficiently for life sciences stakeholders.

​Automation & DevOps Support

​This position serves as a bridge into the world of DevOps. You will assist in automating routine support tasks using scripting languages like Python or PowerShell. You will also gain hands-on experience with industry-standard tools such as Git, Jenkins, and Docker, supporting the maintenance of CI/CD pipelines to streamline deployment processes.

​You are the foundational support for Trinity’s analytical platforms. By combining your burgeoning DevOps skills with a strong focus on SQL data integrity and system uptime, you ensure that complex life sciences data remains accessible and reliable for critical decision-making.