Ankit Sharma
Sr. QA Tester/ETL Tester at Johnson & Johnson
- Role
- Sr Qa Tester Etl Tester at Johnson & Johnson
- Location
- Dallas-Fort Worth, TX, US
- LinkedIn followers
- 500 followers
About Ankit Sharma
Highly accomplished and results-driven Sr. QA Tester/ETL Tester with over 7+ years of…
Experience
Sr Qa Tester Etl Tester
Jul 2022 — Present · San Angelo, TX, US
Validated ETL and BI systems performance under high data volumes, ensuring they meet SLA requirements for batch job execution and reporting.Identify bottlenecks in ETL workflows and recommend optimizations for faster data processing.Provided recommendations to improve ETL processes, testing methodologies, and tools, contributing to overall quality and efficiency.Used Databricks for Notebook creation for tables.Used Databricks for Data validation by wring SQL queries and python code.Used Databricks for Job monitoring and run the workflows.Hands on experience on defect tracking tool Zephyr.Performed incremental and full data load testing to ensure data accuracy, completeness, and consistency.Tested and validated data pipelines in AWS, and Databricks, ensuring seamless data processing and storage for large volumes of pharma data.Developed and execute SQL queries to test data pipelines, perform data validation, and troubleshoot issues in AWS-hosted environments, ensuring scalability and reliability of ETL processes for production systems.Conducted schema validation, indexing verification, and query optimization to ensure efficient data retrieval for pharmaceutical reports.Implemented basic PySpark, Python scripts to automate repetitive testing tasks and validate data integrity in large datasets.Debug and analyze data processing issues in PySpark scripts, verifying transformations and logic applied on distributed datasets.Used Python to analyze and troubleshoot data discrepancies, validate source-to-target mappings, and create reusable scripts for testing ETL pipelines efficiently and reliably.Key AchievementsSuccessfully identified and resolved critical issues in ETL workflows ensuring 100% accuracy in clinical trial and patient data reporting. This improvement enabled compliance with FDA and HIPAA regulations, reducing audit findings to zero.
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