Santosh Kumar Email & Phone Number

United States

Sunnyvale, California, United States

With extensive experience in AWS and big data technologies, I specialize in designing and deploying multi-tier applications utilizing a range of AWS services including EC2, Route53, S3, RDS, Dynamo DB, SNS, SQS, and IAM within AWS CloudFormation. My focus is on ensuring high availability, fault tolerance, and auto-scaling. I have developed robust AWS data pipelines, leveraging AWS API Gateway and Lambda to efficiently store data in JSON format within AWS Redshift. Proficient in Python, I've engineered scalable Lambda code for handling nested JSON files and performing complex operations. Additionally, I excel in building Spark applications with Scala, optimizing performance and efficiency while transitioning from MapReduce to Spark SQL. My expertise extends to real-time data collection from AWS S3 buckets using Spark Streaming, along with implementing AWS Glue for data cataloging and integration. I adhere to Agile methodologies, maintaining Hadoop clusters on AWS EMR and designing reports and dashboards in Tableau for insightful data visualization.

Rockville, Maryland, United States

Having gained extensive experience with the Azure cloud platform, I've worked extensively with services such as HDInsight, Data Lake, Databricks, Blob Storage, Data Factory, Synapse, SQL, SQL DB, DWH, and Data Storage Explorer. My role involves designing and setting up Azure Cloud relational servers and databases to meet both current and future business needs. I specialize in crafting resilient data ingestion pipelines on Azure HDInsight Spark clusters using Azure Data Factory and Spark SQL, as well as processing data efficiently in Azure Databricks. I've successfully constructed scalable ETL pipelines within Azure Data Factory, integrating diverse data sources and loading them into Azure SQL Data Warehouse. Leveraging Python APIs like PySpark, I've unified disparate data sources into a cohesive data mart, employing Snowflake DB and Apache Spark. Additionally, I'm well-versed in Azure DevOps and VSTS for CI/CD, implementing authentication via Active Directory and authorization through Apache Ranger. My collaborative approach includes devising effective branching strategies and utilizing Enterprise GitHub and Azure DevOps Repos for version control. Moreover, I have adeptly developed interactive reports in Power BI tailored to specific client requirements.

Providence, Rhode Island, United States

My expertise revolves around managing the process of extracting, transforming, and loading data. I specialize in gathering various data types from HDFS, covering areas such as customer behavior, sales, revenue, and logistics. Using Apache NiFi, I smoothly transfer this data to AWS S3, ensuring its quality through thorough validation and cleansing using Python scripts. Through PySpark, I carry out extensive data processing and conversion tasks before directing the refined data to AWS RedShift for analysis. I efficiently schedule and coordinate these data pipelines using Apache Oozie. Moreover, I've led a team effort to conceptualize and implement complex data ingestion and processing pipelines, resulting in a significant 50% reduction in insight-generation time. I am adept at analyzing data with Apache Hive and skillfully translate Hive queries into PySpark transformations. Monitoring is effectively performed using Grafana, while GitHub serves as a reliable platform for version control. Additionally, I leverage my expertise to create insightful visualizations and dashboards in Tableau, enhancing reporting and fostering business intelligence endeavors.

St Louis, Missouri, United States

I have a comprehensive background in utilizing Informatica Client tools such as Power Centre Designer, Workflow Manager, Workflow Monitor, and Repository Manager. My responsibilities have included extracting data from diverse sources like Oracle and flat files and developing intricate mappings using Informatica Power Centre. Additionally, I've managed data loading from web servers and Teradata using Sqoop, Flume, and Spark Streaming API. Configuring real-time data pipelines with Kafka for streaming data ingestion and Spark Streaming for processing has been a key aspect of my work. I've also contributed to analytics on live streaming data using Kafka. Furthermore, I have developed MapReduce/Spark Python modules for machine learning and predictive analytics in Hadoop on AWS. Collaborating closely with data modelers, I've contributed to the development of STAR schemas and ensured adherence to ETL standards by reviewing design documents and conducting SQL queries on Repository DB. Additionally, I've leveraged PL/SQL scripts for daily ETL operations and managed Unix Shell Scripts for process enhancement. Lastly, I've converted business requirements into technical design documents and played a role in setting up SFTP with internal bank management while also handling tasks such as data cleanup and sample data loading using SQL Loader and scripts.

Hyderabad, Telangana, India

I bring extensive experience across various projects involving machine learning, big data, data visualization, R and Python development, Unix, and SQL. My expertise lies in quantitative analysis, data mining, and presenting data to unveil trends and insights. Utilizing Python libraries such as Pandas, NumPy, SciPy, and Matplotlib, I conduct exploratory data analysis and perform complex data manipulations. I have a strong command of SQL, creating intricate queries and scripts to extract and aggregate data for validation and business requirements gathering. Proficient in Excel and Tableau, I prepare detailed analysis reports, identifying patterns and outliers. Additionally, I specialize in data quality assessment, performing validation using SQL queries and generating summary reports in Excel. My skills extend to reading data from diverse sources like CSV files, Excel, HTML pages, and SQL, conducting analysis, and writing to various data destinations. Furthermore, I leverage Pandas Data Frame and lambda functions for efficient data operations, along with creating regression test frameworks and implementing business logic through Python backend code.