SaiKishore Narra
Professional Summary
Data Engineer with 5 years of experience building cloud-native ETL and lakehouse solutions on Azure and AWS for healthcare and enterprise analytics. Expert in Microsoft Fabric and Azure Databricks lakehouse patterns using Delta Lake and Parquet, and in designing pipeline orchestration with Dagster and AWS Glue. Skilled in PySpark and Spark SQL for large-scale transformations, T-SQL for database-centric logic, and Python for ETL automation. Experienced in Redshift-based warehousing and SQL Server integrations, with hands-on implementation of IAM, data masking and Microsoft Purview governance controls. Proven ownership of end-to-end data delivery, CI/version control for data artifacts, and production monitoring to ensure reliable, auditable pipelines and faster time-to-insight for business stakeholders.
Technical Skills
Work Experience
- Designed end-to-end ingestion pipelines using Microsoft Fabric Data Factory and Dataflows Gen2, improving data ingestion efficiency by 40%.
- Implemented medallion lakehouse architecture using Delta Lake and Parquet in Microsoft Fabric to standardize Bronze/Silver/Gold layers for analytics consumers.
- Optimized transformation logic using T-SQL and Spark SQL in Fabric notebooks to simplify complex joins and cleanup rules across large healthcare tables.
- Integrated on-prem OLTP sources (SQL Server) with the lakehouse using Fabric dataflows and incremental load patterns to ensure timely data availability.
- Automated deployment and version control for Fabric notebooks and Dataflows using Git to improve release traceability and rollback safety.
- Enforced data governance and compliance through Microsoft Purview sensitivity labels, RBAC and Azure IAM policies to support masking and audit requirements.
- Architected scalable ETL pipelines on AWS S3, AWS Glue and Amazon Redshift to centralize multi-source client data for analytics.
- Orchestrated asset-based pipelines and schedules using Dagster to improve visibility, lineage and recoverability of data jobs.
- Developed Python ETL scripts for Glue jobs and optimized SQL-based data models on Redshift to improve reporting query patterns.
- Automated failure detection and remediation using AWS Lambda-driven alerts, improving pipeline reliability by 35%.
- Built interactive Power BI and Tableau dashboards and delivered reusable data marts to reduce time-to-insight for stakeholders.
- Implemented AWS IAM least-privilege roles and access controls to enforce secure data access across environments.
Projects
- Engineered an end-to-end RCM pipeline in Azure Databricks that integrated EMR, claims, and provider NPI datasets into a Delta Lake gold layer.
- Designed PySpark transformations and cleansing logic to compute AR aging and collection efficiency KPIs used by finance teams.
- Implemented incremental loads, partitioning and audit trails in Delta Lake to reduce processing overhead and maintain lineage.
- Produced gold-layer tables consumed by Power BI to automate billing and claim-status reporting for revenue optimization.
Education
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