Hitesh Kumar
About Candidate
Data Engineer and Analytics Professional with 9+ years of experience delivering data-driven solutions across telecom, healthcare, and retail domains. Proven track record of designing scalable data pipelines, automating complex data workflows, and transforming raw data into actionable insights that support business operations and decision-making. Experienced in building enterprise data platforms, implementing data quality and profiling frameworks, and developing analytics services that improve data reliability, reporting efficiency, and operational performance.
Location
Education
Work & Experience
• Designed and deployed enterprise-scale data pipelines enabling automated ingestion and transformation of
large business datasets.
• Worked with cloud-based data platforms including Azure Data Factory and Databricks to support scalable data
processing and analytics workflows.
• Optimized production data pipelines and workflows, reducing data refresh time by 30% and improving
reporting efficiency.
• Developed data profiling APIs using FastAPI and Python to generate automated dataset statistics and metadata
insights.
• Implemented column profiling, categorical analysis, and metadata tagging using Python and Pandas.
• Automated metadata ingestion and validation processes improving analytics readiness across enterprise
datasets.
• Delivered 20+ production pipelines with stable deployments and minimal post-production defects.
• Developed Python-based modules for automated data extraction, transformation, and validation.
• Optimized legacy scripts reducing execution time by 40%.
• Built reusable Python utilities for data cleansing and transformation
• Developed Power BI dashboards to track sales, inventory, and customer trends.
• Automated reporting processes using Excel and Power BI dashboards.
• Data-driven analysis contributed to ~15% improvement in marketing ROI.
• Built Python and SQL scripts to analyze telecom network performance datasets.
• Generated SQL-based analytical reports supporting optimization teams.
• Improved optimization accuracy by 20% through data-driven analysis.
• Collected and analyzed telecom network performance data to evaluate coverage and service quality.
• Generated analytical reports supporting network optimization and planning decisions.
