Suhas S murthy

I’m an analytically rigorous Data Analyst with 4 years of hands-on experience in ETL/ELT pipeline engineering, statistical analysis, and business intelligence (BI) delivery across US healthcare domains. I translate raw, large-scale datasets into KPI dashboards, data visualizations, and data storytelling that drive measurable decisions.

At Harman Connected Services (Wipro Subsidiary), I spearheaded end-to-end ETL/ELT pipeline architecture using Python, PySpark, Apache Spark, SQL, and GCP—ingesting 10M+ healthcare records into BigQuery while reducing data ingestion latency by ~35%. I also built reusable BigQuery views and curated analytical datasets that accelerated BI adoption across 3 business units, cutting report-preparation time by ~30%.

I’m particularly strong in statistical analysis and exploratory data analysis (EDA). By building Python-based data validation and outlier-detection pipelines across 12+ healthcare datasets, I reduced claim-processing discrepancies by ~20%, improving downstream decision accuracy.

I balance performance optimization, reliability, and compliance: I tuned BigQuery with partitioning/clustering and query restructuring to cut query runtime by ~40% and compute spend by ~25%, while maintaining <1% error rate on 10M+ transaction records across 3 external compliance audits. I also architected and maintained 15+ Apache Airflow DAGs to reduce manual intervention by ~60%, embedding GitHub-based pipeline testing and schema enforcement throughout the workflow.