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Bharat Agrawal

@bharatagrawal

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Senior Data Engineer at Persistent Systems building reusable Azure Lakehouse pipelines and data models.

India

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At Persistent Systems, I design ETL/ELT pipelines and reusable Databricks workflows across diverse data sources. I developed data quality checks that improved reliability by over 60% and optimized Spark jobs and SQL queries to improve processing performance by 30%.

At Nagarro, I architected a cloud data migration for a microfinance client, moving on-premises reporting to an Azure Lakehouse. I also designed data models with SCD Types 1/2/3 and implemented PII masking and data governance strategies. I’m certified in Databricks data engineering and Azure data engineering.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer / Engineer Lead

Current

Persistent Systems

Dec 2023 - Present (2 years 9 months)

Designed and implemented automated ETL/ELT pipelines using ADF, Databricks, DBT, Python, and PySpark, reducing manual errors by 12%. Led architecture optimization and CI/CD adoption, improving data reliability and processing performance.

Azure Data Factory Databricks DBT Python PySpark SQL Delta Lake Azure DevOps CI CD Data Modeling Spark Optimization Data Quality

Data Engineer

Nagarro

Sep 2021 - Dec 2023 (2 years 3 months)

Architected end-to-end cloud data migration for a BFSI client to Azure Lakehouse, enabling unified reporting. Designed data models with SCD types and enforced PII masking and governance.

Azure Databricks PySpark ADF Data Modeling SCD PII Masking Data Governance Data Archival Team Leadership

Senior Software Engineer

PromptCloud

Mar 2020 - Apr 2021 (1 year 1 month)

Engineered large-scale web crawling infrastructure for high-volume data acquisition and implemented quality assessment frameworks to ensure data accuracy.

Web Crawling Data Quality Python Distributed Systems

Software Engineer

Oceanfrogs Consulting Pvt. Ltd.

Feb 2019 - Mar 2020 (1 year 1 month)

Designed and executed analyses on large data volumes, building aggregation and disaggregation models to convert raw multi-format data into structured, analytics-ready datasets.

Data Analysis Data Modeling SQL Python