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Software Development Engineer with 5+ years in Data Analytics & Business Intelligence
AI is analyzing your overall score…
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Techno-functional Software Development Engineer with strong expertise in data analytics, business intelligence, and stakeholder management. Experienced in designing and delivering interactive dashboards using Power BI and Spotfire, while bridging the gap between business needs and technical solutions. Proven ability to drive data-driven decision-making through analytics, reporting, and predictive modeling. Passionate about solving complex problems and delivering impactful insights.
Visvesvaraya Technological University
BE · Mechanical Engineering
N/A – June 30, 2019
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Cultural Fit Analysis
The candidate's diverse experience, including roles in mechanical engineering before transitioning to data science and software development, indicates adaptability and a willingness to learn new domains. Their focus on business intelligence, data analytics, and stakeholder management aligns well with roles requiring strong analytical and communication skills. The breadth of skills across data visualization, SQL, Python, and business analysis suggests a versatile individual who can contribute to various aspects of a data-driven team. However, the target role 'Software Development Engineer' might require a deeper dive into core software engineering principles, data structures, algorithms, and system design, which are not explicitly highlighted in their current experience.
Soft Skills & Operational Fit
The candidate demonstrates strong business acumen, stakeholder management, and communication skills, acting as a bridge between technical and business teams. Their experience in delivering executive-level presentations and actionable insights suggests a proactive and results-oriented approach. The ability to work with cross-functional teams indicates good collaboration skills. However, the career transition from mechanical engineering to software development/data science is relatively recent, which might imply a learning curve in pure software engineering best practices.