● Engineered scalable data pipelines utilizing Apache Spark and Python, processing and cleansing large volumes of data monthly, optimizing performance. ● Automated data ingestion, transformation, and loading workflows with Python, dbt, and Apache Airflow, reducing manual effort by 40%. ● Led migration of critical datasets to AWS cloud using AWS Glue and EMR, achieving a reduction in data processing time. ● Extended and deployed end-to-end machine learning models on AWS SageMaker, enhancing predictive accuracy by 15% through advanced feature engineering and hyper parameter tuning. ● Architect AWS infrastructure with Terraform, facilitating seamless deployment orchestration via Jenkins and Urban Code Deploy, improving deployment efficiency.

● Spearheaded data extraction and transformation initiatives using Azure Data Factory (ADF), resulting efficiency improvement in ETL processes. ● Applied scalable data cleaning solutions with Pandas and PySpark, reducing data inconsistencies by 15% and enhancing overall data quality. ● Designed and optimized databases, leveraging advanced SQL techniques such as partitioning and clustering, leading to improvement in query performance. ● Developed interactive dashboards and reports in Power BI, enabling real-time data visualization and decisionmaking, contributing to a 25% increase in data accessibility. ● Collaborated within Agile Scrum teams, utilizing Jira for project management, ensuring timely delivery of data solutions and achieving a reduction in project turnaround time.

● Constructed scalable big data pipelines leveraging Apache Spark and Airflow, ensuring efficient ingestion, transformation, and loading of massive datasets, optimizing processing time. ● Established and maintained a robust data lake infrastructure on AWS S3, enhancing storage and retrieval capabilities for diverse datasets, resulting in 25% faster data access. ● Empowered data analysts with interactive querying capabilities using Hive and Presto, enabling real-time data insights and driving data-driven decision-making processes for clients. ● Orchestrated real-time data processing pipelines with Apache Kafka, managing high-velocity data streams with uptime, ensuring timely insights for critical analytics applications. Project: ● Real-time Data Processing Platform.