Data Engineer with 3+ years in Data Integration & Analytics
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Assessing your cultural and operational fit
Data Analyst / Data Engineer with 3 years of experience in data integration, analytics, and workflow automation. Specialized in Power BI, Informatica IICS, SQL, and PostgreSQL, with proven expertise in designing analytical reports, optimizing ETL pipelines, and implementing workflow orchestration using Automic (Automation Engine). Adept at troubleshooting data issues, performing root cause analysis, and ensuring high data accuracy to support business-critical operations and analytical initiatives.
College of Engineering, Guindy
Master of Engineering (M.E.)
August 1, 2019 – June 30, 2021
ICON
Data Engineer
December 1, 2025 – Present
Chennai, Tamil Nadu, India
AVASOFT
Associate Data Analyst
March 1, 2023 – April 1, 2024
Chennai, Tamil Nadu, India
Microsoft Certified: Power BI Data Analyst Associate
Microsoft
June 1, 2026 – Present
Microsoft Certified: Fabric Analytics Engineer Associate
Microsoft
June 1, 2026 – Present
Databricks Certified Data Engineer Associate
Databricks
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's experience across two companies, including a current role as a Data Engineer, shows stability and progression. The diverse set of certifications (Microsoft Power BI, Fabric Analytics, Databricks) indicates a proactive approach to skill development and a broad interest in modern data engineering tools, which aligns well with a culture of continuous improvement and technological adoption. The focus on clinical data projects also suggests an ability to work in regulated environments.
Soft Skills & Operational Fit
The candidate's resume highlights strengths in analytical and problem-solving skills, communication, teamwork, and a focus on quality. These attributes suggest a good operational fit for roles requiring collaborative problem-solving and meticulous data handling. The experience in both development and support activities indicates adaptability and a comprehensive understanding of the data lifecycle.