With 3+ years of experience in Data Engineering, I have successfully designed, developed and maintained the data pipeline, resulting in a 42% reduction in data processing time. By automating ETL processes and using effic…
With 3+ years of experience in Data Engineering, I have successfully designed, developed and maintained the data pipeline, resulting in a 42% reduction in data processing time. By automating ETL processes and using efficient workflows, I improved data accuracy by 26%.
With 3+ years of experience, excelled in data engineering roles at Persistent Systems and Zimetrics
Technologies,
Maintained data pipeline up-time of 99.8% while ingesting data across different data sources using
Spark, SQL, Athena, S3, Aurora, Airflow, EMR and Python.
Increasing data processing efficiency by 50%, reducing manual workload by 29%, and driving data
accuracy by 20%. Implemented scalable pipelines, resulting in 50% faster processing time, and saved
$100K annually. Proven track record of delivering results in just 3 years.
<p>Successfully converted on premise data pipeline to BigQuery, resulting in a 50% increase in data processing efficiency.<br>
Streamlined processes by 30% by understanding business functionality and analyzing business requirements leading to a 25% increase in productivity.<br>
Achieved 20% increase in data accuracy through BigQuery validation and testing, driving improved decision-making.<br>
Successfully loaded and transformed 10,000+ data records into BigQuery using Kronos ETL tool, ensuring accurate and timely data for analysis.<br>
Revised reporting efficiency by 50% using Looker Studio resulting in faster data validation and increased productivity.<br>
Implemented raw, base, and compute layers in BigQuery Database, improving data storage capacity by 50%.<br>
Boosted project completion rate by 15% and optimized project management through Jira ticket tracking system.<br>
Git Code repository was used to maintain the code.<br>
Designed Data Pipeline workflows for efficient extraction, transformation, and loading, which reduced data processing time by 42%.<br>
Crafted and deployed data governance plan resulting in 95% reduction in data errors and elevated data quality for reporting.</p>
<p>Maintained data pipeline up-time of 99.8% while ingesting data across different data sources using Spark, Athena, S3, Aurora and Python.<br>
Automated ETL processes across billions of rows of data, which reduced manual workload by 29% monthly.<br>
Enhanced data ingestion process by 50%, utilizing SQL for faster and more efficient data retrieval, leading to improved decision-making.<br>
Google API, Facebook API using Php, Python to create data views to be used in BI tools like Tableau.<br>
Communicated with project managers and analysts about data pipelines that drove efficiency KPIs up by 26%.<br>
Implemented scalable data pipeline, reducing data processing time by 50% and saving $100K annually.<br>
Developed data quality checks, reducing data errors by 75% and ensuring accurate and reliable data for decision making.</p>
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