Data engineering professional poised to add significant value through comprehensive experience in developing scalable data solutions. Noted for strong team collaboration and adaptability in fast-paced environments. Reliable in driving results with key skills in data modeling, ETL processes, and cloud-based data platforms.
Overview
5
5
years of professional experience
1
1
Certification
Work History
Senior Data Engineer
EPAM
12.2022 - Current
Spearheading the development of a cloud-native data warehousing solution for a major U.S.-based Quick Service Restaurant (QSR) chain, leveraging Snowflake, AWS, Airflow, and Terraform to deliver high-performance analytics infrastructure.
Building robust ETL pipelines to ingest data from diverse sources into AWS, transforming and loading it into Snowflake in a well-structured, analytics-ready format.
Collaborating cross-functionally with client stakeholders and distributed teams to implement scalable, secure, and maintainable data solutions in line with enterprise data governance standards.
Senior Data Engineer
Quantiphi Analytical Solutions Pvt. Ltd.
12.2020 - 01.2024
Data Migration & Transformation: Led a successful migration from Teradata to Snowflake, improving query performance by 50% and reducing data transformation times by converting legacy mappings into optimized Snowflake stored procedures. Utilized dbt to transform and model data within Snowflake, creating streamlined, modular data transformations that improved data accessibility and analytics performance.
Cloud-Based Integration: Architected and deployed ETL pipelines utilizing AWS Redshift, Lambda, Step Functions, and SNS to automate data ingestion into AWS Redshift, reducing manual effort by 40%.
Reconciliation Framework: Engineered a reconciliation framework leveraging SQL, AWS Redshift and AWS Step Function, minimizing financial data discrepancies between on-premise and cloud environments.
Optimized Data Processing: Designed complex SQL queries for data extraction and transformation, improving processing times by 30-40%.
Python: Developed and optimized ETL pipelines using Python, and AWS services (Lambda, Redshift) to manage large-scale data processing across cloud environments.