Data & Analytics Engineer
First seen by Alion on Oct 10, 2026.
The Data & Analytics (D&A) Engineer is responsible for delivering business needs end-to-end in an iterative, agile pattern, starting from understanding the requirements to deploying scalable and robust software, utilizing cloud technology and full automation, into production. This role will solve integration needs by supplying and consuming information needed for analytics and operations. We use a variety of technology, from big data to open-source frameworks including AI/ML, to integrate and present meaningful analytical insights into clinical trial business needs and customer uses. Our tools analyze historical data to identify insights, forecast trends, and recommend actionable items to improve clinical trial business and operations. In addition to delivery, the D&A Engineer should have an automation first and continuous improvement mindset, driving the adoption of CI/CD & data ops tools while supporting the improvement of the tool sets/processes. This role requires being fluent in some technologies while being proficient in others and learning on the job to deliver value to both customers and to the business. Necessary attributes of the position include ownership, accountability, and resilience.
ESSENTIAL DUTIES/RESPONSIBILITIES: To perform this job successfully, an individual must be able to perform each essential duty and responsibility satisfactorily. The accountabilities listed below are representative of the knowledge, skills, and/or ability required.
- Contribute as part of a scrum team on requirements from a business/product owner and take direction from the tech lead.
- Design, implement, test and release(deliver) technical solutions to business requirements.
- Implement automated release (CICD) for solution delivery.
- Actively participate in the agile delivery process.
- Other duties as assigned by supervisor. These may, on occasion, be unrelated to the position described here.
- Attendance and punctuality are essential functions of the position.
EDUCATION REQUIREMENTS: Bachelor's degree in a quantitative discipline (i.e. statistics, applied mathematics, computer science, data mining, machine learning, or some other empirical science) preferred.
QUALIFICATIONS/EXPERIENCE:
- 3+ years of experience in a Data or Analytics role with a proven track record of quality software development in a disciplined software development lifecycle and an ability to innovate outside of traditional architecture/software patterns when needed to deliver customer enterprise or customer facing applications
- 1+ years of experience in the following: covering Big Data, Streaming, and Data Engineering related technologies such as spark, using scripting languages such as Python and using object-oriented languages such as Java/Scala/C++ or functional programming languages such as Scala
- in DevOps/CICD, using technologies such as docker/ kubernetes
- Familiarity with using Databricks or a similar platform for data engineering & data science
- Comfortable in configuring and using multiple operating systems (Mac/Windows/*nix)
- Knowledge and/or experience with health care information domains is a plus
TRAVEL REQUIREMENTS: 0% – 5%