Brandeis University’s Online Information Technology Management Program is seeking an Adjunct Faculty member for RITM 115 Programming for Systems Automation & Data Workflows for the Fall-1 2026 session. This 3-credit asynchronous online course is an 8-week requirement for the Master of Science in Information Technology Management.
Course Description: This course teaches programming fundamentals for systems automation, data processing, and operational task execution. Students build scripts and applications that automate integration tasks, manage data flows, and support system processes within enterprise contexts.
Core Course Responsibilities Summary
Course Logistics and Facilitation: Focuses on the organized and timely rollout of course content, maintaining consistent communication through weekly announcements, and ensuring all instructional activities occur within university-approved digital platforms.
Instructor Presence and Engagement: Centers on building an active teaching persona by hosting live introductory sessions, facilitating weekly academic discourse in forums, and maintaining regular availability for student consultation.
Individual Feedback and Grading: Emphasizes the professional obligation to provide transparent, rubric-based evaluations and supportive commentary on student work within a standardized weekly timeframe.
Professional Conduct and Standards: Requires adherence to university communication protocols, the promotion of respectful online "netiquette," and ensuring the course meets accessibility and technical visibility standards before and during the term.
Qualifications:
Required:
Master’s degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or a closely related field
Minimum 3 years of professional experience in programming for automation, scripting, data processing, or enterprise systems integration
Demonstrated proficiency in programming languages commonly used for automation and data workflows (e.g., Python, PowerShell, Bash, JavaScript)
Experience designing automation scripts, APIs, or data pipeline components within enterprise environments
Minimum 1 year experience developing asynchronous online courses for adult learners in higher education
At least 1 year of teaching or training experience (preferably online/asynchronous)
Experience with online instruction
Excellent communication and teaching skills in an online learning environment.
Preferred:
Doctorate (PhD or DBA) in Computer Science, Software Engineering, Information Systems, Data Engineering, or related field
5+ years of experience in software development, automation engineering, data engineering, or platform engineering leadership
Professional experience as a Software Engineer, Automation Engineer, Data Engineer, DevOps Engineer, or Systems Integration Architect
Experience working with workflow orchestration and data pipeline tools (e.g., Airflow, Prefect, Azure Data Factory, AWS Step Functions)
Industry certifications such as AWS Developer Associate, Azure Developer Associate, Certified Kubernetes Application Developer (CKAD), or equivalent
Prior online teaching experience at the graduate level
Knowledge of global learner personas and culturally responsive pedagogy
Familiarity with Moodle LMS and digital authoring tools (e.g., H5P)
Interested candidates should submit:
A cover letter highlighting relevant qualifications and teaching experience.
A current CV or resume.
Contact information for three professional references.
Application review begins 5/28/2026 though we will continue to accept submissions on an ongoing basis.
This appointment is to a position that is in a collective bargaining unit represented by SEIU Local 509.
Compensation for this position is $6573.15
The University's pay ranges represent a good faith estimate of what Brandeis reasonably expects to pay for a position at the time of posting. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience and education/training, internal peer equity, and applicable legal requirements.
Brandeis University is an equal opportunity employer which does not discriminate against any applicant or employee on the basis of race, color, ancestry, religious creed, gender identity and expression, national or ethnic origin, sex, sexual orientation, pregnancy, age, genetic information, disability, caste, military or veteran status or any other category protected by law (also known as membership in a "protected class").
