Open to opportunities

Sithambaravarman Mahendran

@sithambaravarmanmahe

Message

I’m a Data Engineer building Snowflake ETL/ELT pipelines for healthcare and insurance insights.

India

Message

What I'm looking for

I’m looking for a role where I can build Snowflake-first, automated ETL/ELT pipelines for healthcare/insurance domains—using AWS, Kafka, and DBT—while owning data quality, clear dimensional models, and reporting-ready outputs in an agile team.

I’m a Data Engineer with 3.4 years of experience working on Snowflake-based data ETL/ELT pipelines across health insurance and healthcare domains. I focus on reliable data movement, validated transformations, and clean delivery to reporting layers.

I’ve migrated insurance data from SQL Server to Snowflake by mapping source tables and columns into Dimensional Modeling (Star / Snowflake). I built staging pipelines with a 3-layer architecture—Raw, Data Vault Modeling Cleansed, and Final—so only validated records reach downstream analytics.

My work also blends automation and real-time ingestion: I configured Snowpipe on AWS S3 for daily loads, implemented Snowflake Tasks and Streams for batch processing, and integrated Kafka streaming to capture insurance premium events. I create Snowflake objects (Views, Materialized Views, stored procedures, and UDFs), support Power BI reporting, and validate data quality using SQL logic and Python scripts.

Experience

Work history, roles, and key accomplishments

Data Engineer

Britapp Systems

Feb 2023 - Jul 2025 (2 years 5 months)

Designed a star schema for ESMACS health insurance data using premium and payment fact tables with policy, sponsor, and coverage dimensions. Built Snowflake ETL/ELT pipelines from SQL Server to Snowflake using Snowpipe and AWS S3, with a 3-layer (Raw/Cleansed/Final) validation approach to ensure only clean records reached reporting.

Snowflake Snowpipe DBT AWS S3 Python Kafka Star Schemas Power BI

Associate Data Engineer

Capminds

Sep 2021 - Jul 2022 (10 months)

Supported a telehealth application by storing appointment, e-prescription, next schedules, and consultation records in Snowflake. Built Snowflake views for doctor and patient reporting, used ROW_NUMBER()-based logic to detect duplicate bookings, and ran UAT verification queries to confirm appointment data accuracy before go-live.

Snowflake Data Validation Data Reconciliation