Hareesh Vangari Email & Phone Number

Chicago, Il, Us

Kansas, United States

I specialize in designing and implementing robust data pipelines using Microsoft Azure, leveraging technologies like Azure Data Lake Storage, Azure SQL Database, and Azure Blob Storage. My expertise extends to extracting and transforming data from various sources including Oracle Financials and DynamoDB, utilizing tools such as Azure Data Factory and SSIS for efficient ETL processes. I am proficient in optimizing data workflows with Python scripts and Spark jobs, ensuring high data quality and performance across large-scale datasets.I have a strong background in developing and optimizing ETL pipelines, both in traditional and cloud environments, focusing on enhancing data integrity and operational efficiency. I excel in leveraging Python for complex data transformations and in developing Spark applications to process and integrate diverse data sources. Additionally, my experience includes managing Hadoop clusters and implementing SQL and NoSQL databases like MongoDB and PostgreSQL for scalable and high-performance data storage solutions.Furthermore, I am skilled in creating interactive visualizations and reports using Power BI and Tableau, enabling stakeholders to derive actionable insights from complex datasets. My approach emphasizes collaboration across teams using Git and Jira for version control and project management, ensuring seamless integration and alignment with project goals and timelines.

Cincinnati, Ohio, United States

I specialize in AWS cloud services and data engineering, adept at leveraging AWS CLI for Auto Scaling and CloudWatch setup, and managing CloudTrail for comprehensive AWS environment monitoring. I ensure data security by implementing S3 bucket versioning for sensitive information and utilize DynamoDB integrated with AWS Lambda for scalable data storage and backup. My expertise extends to data ingestion automation using PySpark and Scala from diverse sources like APIs, AWS S3, Teradata, and Redshift, facilitating seamless data processing and migration to AWS. I've successfully migrated on-premises applications to AWS, employing EC2 and S3 for efficient data processing and storage, and maintaining Hadoop clusters on EMR.In data engineering, I design and implement end-to-end ETL and ELT pipelines using PySpark, ensuring robust data extraction, transformation, and loading into centralized warehouses. I optimize data processing with Python and Spark, handling large-scale datasets effectively and integrating machine learning models for advanced analytics. Proficient in SQL and NoSQL databases including PostgreSQL, MongoDB, and Cassandra, I develop optimized queries, manage schema designs, and ensure data integrity across diverse environments. Additionally, I create interactive visualizations and reports using Power BI and Tableau, enabling stakeholders to derive actionable insights from data.I collaborate closely with cross-functional teams using Git and Jira for version control and project management, ensuring smooth integration and deployment of data solutions. My goal is to drive data-driven decision-making through scalable and efficient data pipelines, optimizing performance and enabling impactful insights for business growth and innovation.

Mumbai, Maharashtra, India

I have led the design and architecture of multiple data pipelines, focusing on end-to-end ETL and ELT processes using Azure and Spark technologies. My expertise spans leveraging cloud and GPU computing for automating machine learning pipelines and scalable data processing in Azure. I excel in all stages of data mining, from collection to visualization, and have developed reusable REST APIs to integrate diverse data sources, guided by direct input from business stakeholders. With a background in SQL, Python scripting, and API integration, I ensure robust software delivery through actionable insights gained from gap analysis.In addition, I specialize in Data Warehouses and Business Intelligence architectures, managing full data loads and migrations to Azure environments with meticulous attention to data integrity and reliability. I excel in Spark job development within Azure, using Python for data analysis and transformation. My proficiency extends to scripting, web scraping, and SQL query writing, supporting large-scale data processing and analytics initiatives, and creating robust data pipelines for efficient workflows and scalable performance in cloud environments.

Delhi, India

I have extensive experience in deploying and managing Hadoop clusters in cloud environments, particularly on Amazon EC2 using Whirr. I've demonstrated proficiency in setting up and configuring clusters, ensuring efficient data processing through job management and scheduling. My expertise includes commissioning and decommissioning nodes, recovering namenodes, and optimizing cluster performance through capacity planning and configuration adjustments. Additionally, I specialize in leveraging Hadoop ecosystem tools like Pig, Hive, HBase, and Sqoop for data storage, querying, and integration, showcasing strong scripting skills with Pig scripts and Hive UDFs for complex data processing and analysis tasks.Furthermore, I excel in data handling and analytics, managing large datasets of varied formats within Hadoop environments. I have a robust background in developing and implementing test-driven development processes, ensuring high data quality and reliability. Additionally, I am proficient in ETL processes using Sqoop to export analyzed data to relational databases for visualization and reporting. My skills extend to using Python, R, and data visualization tools such as Tableau and Power BI to create insightful visualizations and reports, enabling effective data-driven decision-making across projects.