Arvapelly Ashrith

I’m a data engineer building end-to-end enterprise ETL pipelines that turn SAP and other operational data into analytics-ready datasets for BI and reporting. I focus on reliable ingestion, robust transformations, and governance so stakeholders can trust the numbers they use every day.

In my current role, I architect enterprise pipelines with Alteryx, SQL Server, Snowflake, and Qlik across DEV/TEST/PROD. I’ve engineered incremental load, CDC, and SCD Type 2 frameworks to support historical tracking, audit compliance, and accurate trend analysis at scale.

I also optimize performance and data quality—reducing pipeline execution time by 35%+ through partitioning strategies, filter pushdown, and parallel processing. I build validation checks that improved data accuracy by ~25%, and I deliver Power BI semantic models supporting 8+ business reports.

Before this, as a Data Engineer Intern, I worked on scalable ETL in Databricks, using PySpark to transform and load 1M+ records per day and reduce processing time by ~30%. I bring practical expertise in orchestration and cloud data engineering, backed by certifications including Power BI Data Analyst Associate, Alteryx Designer Core, and Databricks Certified Data Engineer Associate.