Adjunct Instructor in Data Engineering and Cloud Pipelines

Brandeis University•Waltham, MA

5d•$6,573•Remote

About The Position

Brandeis University’s Online Applied Data Science and Decision Analytics Program is seeking an Adjunct Faculty member for RADS 115 Data Engineering and Cloud Pipelines for the Fall 1 2026 session. This 3-credit asynchronous online course is an 8-week requirement for the Master of Science in Applied Data Science and Decision Analytics. This course will explore concepts of data architecture, ETL/ELT design, and streaming analytics. Includes modules on sustainable data centers and carbon-efficient computation.

Requirements

Advanced degree (Masters or Ph.D) in Computer Science, Data Science, Information Systems, Software Engineering, or related field.
Industry Experience: Building or Managing Cloud Data Platforms.
Experience in Data Engineering and Cloud-Based Data Pipelines, including data architecture and data reliability.
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.

Nice To Haves

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).

Responsibilities

Organized and timely rollout of course content.
Maintaining consistent communication through weekly announcements.
Ensuring all instructional activities occur within university-approved digital platforms.
Building an active teaching persona by hosting live introductory sessions.
Facilitating weekly academic discourse in forums.
Maintaining regular availability for student consultation.
Providing transparent, rubric-based evaluations and supportive commentary on student work within a standardized weekly timeframe.
Adherence to university communication protocols.
Promotion of respectful online "netiquette".
Ensuring the course meets accessibility and technical visibility standards before and during the term.