Radhika Nalawade

Pune, Maharashtra, India

Since April 15, 2026

Data Engineering

4+ years of experience in designing and optimizing scalable ETL pipelines and advanced data analysis.
Deep expertise in Python, PySpark, SQL, and cloud platforms including AWS (S3, EC2) and GCP (BigQuery, Cloud Storage).
Proficiency in Big Data Frameworks such as Apache Spark, PySpark, Hive, Hadoop, and Sqoop.
Proven track record of delivering measurable performance improvements (up to 40% reduction in processing effort/latency).
Strong capabilities in ETL Pipeline Design, Data Quality & Validation, Data Governance, Data Warehousing, and Exploratory Data Analysis.
Experience with large-scale data processing (50M+ records) and orchestration of Spark jobs on cloud instances.
Project experience in financial data platforms and data pipeline optimization, demonstrating real-world application of skills.
Key achievements include significant improvements in ETL pipeline performance through query tuning, Spark optimizations, and automation.

Cultural Fit Analysis

Based on the provided psychometric test score of 0, there is insufficient data to assess cultural fit.

Soft Skills & Operational Fit

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Assessing your cultural and operational fit

4+ years of experience in designing and optimizing scalable ETL pipelines and advanced data analysis.
Deep expertise in Python, PySpark, SQL, and cloud platforms including AWS (S3, EC2) and GCP (BigQuery, Cloud Storage).
Proficiency in Big Data Frameworks such as Apache Spark, PySpark, Hive, Hadoop, and Sqoop.
Proven track record of delivering measurable performance improvements (up to 40% reduction in processing effort/latency).
Strong capabilities in ETL Pipeline Design, Data Quality & Validation, Data Governance, Data Warehousing, and Exploratory Data Analysis.
Experience with large-scale data processing (50M+ records) and orchestration of Spark jobs on cloud instances.
Project experience in financial data platforms and data pipeline optimization, demonstrating real-world application of skills.
Key achievements include significant improvements in ETL pipeline performance through query tuning, Spark optimizations, and automation.

Cultural Fit Analysis

Based on the provided psychometric test score of 0, there is insufficient data to assess cultural fit.

Soft Skills & Operational Fit