Exploring Collaboration Between Engineers, Data Scientists, and Environmental Specialists in Sustainable Technology Development
Keywords:
sustainable technology, interdisciplinary collaboration, engineers, data scientists, environmental specialists, qualitative research, Brazil, thematic analysisAbstract
This qualitative study aimed to explore how engineers, data scientists, and environmental specialists collaborate in the development of sustainable technologies in Brazilian organizational and project contexts. A qualitative descriptive design was used to examine professional experiences of interdisciplinary collaboration in sustainable technology development. Data were collected through semi-structured interviews with 27 participants from Brazil, including engineers, data scientists, and environmental specialists involved in renewable energy, circular economy, water management, environmental monitoring, smart-city, and climate-analytics projects. Participants were selected purposively to ensure disciplinary diversity and direct experience in collaborative sustainability-oriented technology projects. Interviews were conducted online and face-to-face, lasted between 45 and 75 minutes, and continued until theoretical saturation was reached at the twenty-fourth interview, followed by three confirmatory interviews. Audio recordings were transcribed verbatim and analyzed using thematic analysis supported by NVivo software. Five main categories were identified: shared sustainability problem framing, translation across disciplinary languages, data-mediated integration, negotiation of technical-environmental trade-offs, and organizational conditions for collaborative innovation. Participants described collaboration as most effective when teams moved beyond sequential expert contribution and developed shared problem definitions, common indicators, and iterative feedback loops. Data dashboards, environmental impact models, prototypes, and regulatory matrices functioned as boundary objects that helped professionals coordinate without eliminating disciplinary differences. However, collaboration was constrained by incompatible timelines, different evidentiary standards, fragmented data ownership, and tensions between engineering feasibility, algorithmic performance, environmental integrity, and commercial pressure. Sustainable technology development depends not only on advanced technical expertise but also on structured interdisciplinary collaboration. The findings suggest that engineers, data scientists, and environmental specialists need shared evaluative frameworks, translational routines, participatory data governance, and organizational support to integrate environmental knowledge into technology design. Strengthening these collaborative capabilities can improve the relevance, legitimacy, and sustainability performance of emerging technologies.
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