Data Systems DevOps Engineer

Position Title: Data Systems DevOps Engineer

Intro

At Azenta, new ideas, new technologies and new ways of thinking are driving our future. Our customer-focused culture encourages employees to embrace innovation and challenge the status quo with novel thinking and collaborative work relationships. 

Azenta Life Sciences is a global leader in the life sciences space with headquarters in Burlington, MA, and offices and operations worldwide. We are a market leader in automated bio sample management solutions and genomic services across areas such as drug development, clinical and advanced cell therapies for the industry's top pharmaceutical, biotech, academic and healthcare institutions globally.   We provide unparalleled capabilities with our lab analysis, sample management and storage services, informatics software, and consumables, with the largest installed base managing over 1 billion samples globally.

What You’ll Do 

• A core member of the Data Systems team, whose responsibility includes the design, development, testing, deployment, & maintenance of cloud, on-prem, and/or hybrid high-throughput, high-performance, and efficient data systems.

• Directly contribute to the development and maintenance of automated data ingestion, analysis, and delivery systems.

• Design and validate production-grade, i.e., robust, secure, scalable, and cost-efficient infrastructures for various large-scale data applications (e.g., bioinformatics & genomics data).

• Develop and validate efficient and maintainable deployment-automation solutions for various data systems.

• Collaborate with internal and external team members in the development of production data management systems.

• Maintain production-grade codebase and documentation.

• Mentor & train junior team members.

What You Will Bring

• Minimal bachelor's degree in Computer Sciences, Software Engineering, Electronics Engineering, Network Engineering, Bioinformatics, Computational Biology, or an equivalent field.  Advanced degrees and relevant professional certifications a bonus.

• Subject matter expert in DevOps, SysOps, data system design, and/or analysis automation concepts and best practices.

• At least 5 years of relevant industry work experience in developing production-grade data systems, e.g., data ingestion, data management, data analysis, and/or data delivery.

• Thorough understanding of key components of a data system, including storage, computational, network, security, etc.

• Firm grasp of advantages and disadvantages of cloud and on-premises IT solutions.

• Strong knowledge of system performance optimization strategies, and system security best practices.

• Proficiency in AWS development, deployment, monitoring, and automation.

• Associated or Professional level AWS Certifications preferred but not required.

• Proficiency in Python programming language.

• Proficiency in designing and developing database-based applications (e.g., PostgreSQL and/or MySQL based).

• Proficiency in developing and deploying applications for Linux OS.

• Proficiency in IT automation tools like Terraform, Ansible, and/or CloudFormation.

• Proficiency with Git version control.

• Proficiency with Docker concepts and operations (e.g., building Docker Image, commonly used Docker Image optimization techniques, and deploying applications via Docker).

• Familiar with Software Development Life Cycle (SDLC) process, and the associated testing, documentation, & deployment best practices.

• Familiar with Conda operations.

• Understand software documentation best practices, and demonstrable good software documentation habits and abilities.

• Good verbal and written communication skills.

• Good interpersonal skills, and team player.

EOE M/F/Disabled/Vet

Azenta is an Equal Opportunity Employer. This company considers candidates regardless of race, color, age, religion, gender, sexual orientation, gender identity, national origin, disability or veteran status.

The posted pay range for this position is an estimate based on current market data and internal pay structure. Final compensation may vary above or below this range depending on factors such as experience, education (including licensure and certifications),  qualifications, performance, and geographic location, among other relevant business or organizational needs.