Aksh Surani

Data Engineer with 1.5+ years of experience designing, building, and optimizing production-grade ETL/ELT pipelines on Azure and AWS within a US Healthcare environment. Experienced in developing scalable data integration solutions using Snowflake, Azure Data Factory (ADF), Apache Airflow, dbt, Python, and SQL. Built automation solutions that reduced schema onboarding time by ~85% through automated SQL Server-to-Snowflake DDL generation, while improving pipeline reliability with audit and monitoring frameworks.

Skilled in data warehousing, Medallion Architecture (Bronze → Silver → Gold), SCD Type 1 & Type 2, Change Data Capture (CDC), relational data modeling, and workflow orchestration.

Data Engineer - Inferenz - Ahmedabad

(2025-06)

US Healthcare Domain

• Designed and deployed production-grade ETL pipelines using Azure Data Factory (ADF), ingesting data from heterogeneous source systems including REST APIs, SFTP, and SQL Server into ADLS Gen2 following Medallion Architecture (Bronze → Silver → Gold).
• Developed automated Python/SQL scripts to extract table schemas and data types from SQL Server and auto-generate corresponding Snowflake DDL, cutting per-source onboarding effort by ~85% (from ~2 hours to ~20 minutes per source) and eliminating manual scripting.
• Migrated Snowflake stored procedures and transformation logic to dbt (Data Build Tool), improving code modularity, version control, maintainability, and enabling systematic data quality testing across the warehouse.
• Implemented Snowflake Dynamic Data Masking with column-level security to protect sensitive patient information, ensuring only authorized roles could access Protected Health Information (PHI) in compliance with HIPAA data governance and security requirements.
• Built ADF audit pipelines to track pipeline execution status, capture failure metadata, and enable proactive monitoring, improving operational visibility and reducing production troubleshooting time.

Data Engineering Intern - Inferenz - Ahmedabad

(2024-12 - 2025-05)

• Applied Snowflake features including Time Travel, Role-Based Access Control (RBAC), Streams, and Stored Procedures to support real-time change detection, governed data access, and point-in-time data recovery.
• Implemented SCD Type 1 & Type 2 and Change Data Capture (CDC) using Snowflake Streams to maintain historical accuracy and enable incremental data processing.
• Designed normalized relational data models and built end-to-end ETL workflows using Python and Apache Airflow to automate data ingestion from AWS S3 external stages into Snowflake.
• Developed an end-to-end analytics pipeline integrating AWS S3, Snowflake, Apache Airflow, and Power BI, demonstrating automated data ingestion, transformation, orchestration, and reporting.

Bachelor of Technology - Computer Engineering - Charotar University of Science and Technology (2021-10 - 2025-05)

Higher Secondary Certificate - Nalanda Vidhyalaya (2020-06 - 2021-05)