Azure Cloud Engineer with 2+ years in Data Analytics & Cloud Platforms
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Assessing your cultural and operational fit
Data Analyst & Azure Cloud Engineer with 2+ years of experience in leveraging Microsoft Azure to deliver actionable business insights. Expert in developing automated pipelines via Azure Data Factory and Microsoft Fabric to facilitate trend identification and data-driven decision-making. Proven track record of optimizing ETL/ELT workflows to ensure data accuracy for enterprise-level reporting and analytics.
Sri Ramakrishna Engineering College
Bachelor's Degree · Electronics and Instrumentation
August 1, 2019 – June 30, 2023
LTM
Azure Cloud Engineer
March 1, 2024 – Present
Bengaluru, Karnataka, India
Vestas Wind Technology
Analyst Intern
November 1, 2023 – January 1, 2024
Chennai, Tamil Nadu, India
Databricks Certified Data Engineer Associate
Microsoft & Cloud Certifications
June 1, 2026 – Present
AI Product Management - IBM
IBM
June 1, 2026 – Present
Microsoft Fabric Data Factory - Advanced Data Integration (L300)
Microsoft & Cloud Certifications
June 1, 2026 – Present
Microsoft Fabric Data Factory - Orchestration & UX (L200)
Microsoft & Cloud Certifications
June 1, 2026 – Present
Microsoft Certified: SQL AI Developer Associate (DP 800)
Microsoft & Cloud Certifications
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's experience at LTM as an Azure Cloud Engineer directly aligns with the target role, demonstrating a clear career path and interest in cloud data engineering. The certifications further reinforce this alignment and a commitment to continuous learning in relevant technologies. The project diversity is limited to data engineering within Azure, but the depth of experience in this specific domain is strong. The candidate's profile suggests a good cultural fit for a role focused on data-driven solutions within the Azure ecosystem.
Soft Skills & Operational Fit
The candidate's experience descriptions indicate strong analytical and problem-solving skills, particularly in identifying operational inefficiencies and optimizing data workflows. The ability to communicate analytical insights to both technical and non-technical teams suggests good communication and collaboration skills. The focus on data accuracy and governance aligns well with operational best practices.