Hemanth K Email & Phone Number

Raleigh, Nc, Us

Westlake, Ohio, United States

I have extensive experience in data engineering and analytics, having managed data extraction, transformation, and loading (ETL) processes across various Azure services including Azure Data Factory, Azure Data Lake, and Azure SQL. My expertise encompasses utilizing tools like T-SQL, Spark SQL, and U-SQL to refine and structure data, implementing pipelines to integrate and transform data from diverse sources, and creating metadata reports using SSRS. Additionally, I’ve developed and maintained SSIS packages for ETL processes, and I’m skilled in debugging and troubleshooting using Informatica Cloud (IICS) transformations.In the realm of big data and machine learning, I have leveraged Apache Spark with Python to execute analytics and machine learning applications, optimizing algorithms with Spark Core, Spark SQL, and Spark Streaming. I’ve utilized Spark Streaming to process near-real-time data from Kafka and stored it in HBase. My experience also includes optimizing Hive queries, performing analytics with Hadoop YARN, and handling large-scale data transformations with PySpark. Furthermore, I’ve implemented various data quality scripts and visualizations using SQL, Hive, Python, and Tableau to ensure data accuracy and generate actionable insights.My database management skills extend across multiple platforms including MySQL, PostgreSQL, MongoDB, and Cassandra. I’ve developed complex SQL queries and database schemas to improve performance and data integrity, configured PostgreSQL instances for high availability, and executed ETL processes using SQL and Python. Additionally, I’ve worked with Snowflake and Power BI to develop and transform data for visualizations, and I’ve implemented Git and Jira to manage version control and agile development processes effectively.

Richmond, Virginia, United States

With extensive experience in data engineering and cloud computing, I have leveraged AWS services such as EMR and DMS to efficiently handle large-scale data transformations and migrations. My role involved transforming and moving substantial datasets between AWS S3 and other AWS data stores, including DynamoDB, and migrating tables from both homogeneous and heterogeneous databases to the AWS Cloud. I have conducted thorough architecture and implementation assessments of AWS services like Amazon EMR, Redshift, and S3, and developed a standardized ETL framework to ensure reusable logic across projects. Additionally, I actively engaged in unit testing, code reviews, and system documentation to maintain high-quality data processes.In my technical journey, I have been deeply involved in ETL processes, using Informatica for mapping, session, and workflow management, and implementing ETL integration patterns with Python and Spark. I developed a framework for converting Power Enter mappings to PySpark jobs and have experience optimizing algorithms in Hadoop using Spark technologies, including Spark RDDs, Spark-SQL, and Spark MLlib. My work also included migrating data from AWS S3 to Snowflake using Scala and transforming Cassandra, Hive, and SQL queries into Spark transformations for improved performance and processing efficiency.Beyond cloud services and ETL frameworks, I have engineered and maintained relational and NoSQL databases, including MySQL, PostgreSQL, MongoDB, and Cassandra. My expertise extends to optimizing SQL queries, designing scalable NoSQL data models, and integrating data across SQL and NoSQL systems. Additionally, I have worked with Snowflake schemas, data warehousing, and data pipelines using Snow Pipe and Matillion. My role also involved creating impactful visualizations with Power BI and Tableau, preparing and cleaning data to ensure accuracy, and collaborating with cross-functional teams.

Telangana, India

I have extensive experience designing and implementing comprehensive database solutions, particularly within the Azure ecosystem, including Azure SQL Data Warehouse and Azure SQL. I’ve successfully architected and executed medium to large-scale Business Intelligence (BI) solutions utilizing Azure Data Platform services such as Azure Data Lake, Data Factory, and Azure SQL Data Warehouse. My expertise extends to creating effective migration strategies for traditional systems to Azure, using methods like lift and shift and tools like Azure Migrate, along with guiding teams on Informatica best practices for scalable and maintainable ETL solutions.In the realm of data processing and analytics, I’ve leveraged Python for SQL operations and data transformations, while also utilizing Spark for in-memory computations and large-scale data processing. My work with PySpark has involved developing optimized workflows for efficient data transformation, and I have designed Spark-based solutions for complex ETL tasks. Additionally, I have built and maintained scalable Spark applications to handle real-time analytics and batch processing, and I have developed pre-processing jobs to flatten JSON documents and serialize JSON data for storage using Spark SQL.My expertise also includes working with various data technologies and tools. I’ve designed complex SQL queries and stored procedures for efficient data processing, and I have developed and optimized data pipelines using NoSQL databases like MongoDB and Cassandra. I’ve installed and configured Apache Airflow for orchestrating workflows with Snowflake and designed interactive Power BI and Tableau dashboards for effective data visualization. Throughout my career, I have ensured seamless data integration across SQL and NoSQL systems, and have implemented Git workflows to streamline development processes.

Haryana, India

I leveraged SQL queries to efficiently extract, analyze, and report data from various data warehouses and AWS services, ensuring precise data retrieval and valuable insights. I developed Python scripts to integrate data from multiple sources, including AWS, and utilized metadata cataloguing to maintain comprehensive data definitions and uphold data integrity. Additionally, I applied R and Python for data transformation, cleaning, and enrichment within AWS environments, automating processes to improve data quality and consistency across datasets.In managing and transforming large datasets, I utilized AWS scalable data processing tools and frameworks like Amazon Redshift to ensure seamless data integration and reporting. I collaborated with Data Modellers and Business Analysts to gather requirements and assess the impact of data analysis on business operations, producing detailed analytical reports and documentation. Implementing data quality frameworks and conducting thorough validation were key to ensuring accuracy and completeness in various analytical systems.I also employed data ingestion tools and APIs, such as Kafka and Hadoop, to support effective data integration and analysis from diverse sources. I optimized data models in Power BI and Excel, created actionable insights for reporting dashboards, and managed version control systems like Git for efficient code organization. Additionally, I provided training on project management tools like JIRA, utilized Jupyter Notebook for interactive data analysis, and applied Google Analytics and IBM SPSS for web data tracking and statistical analysis, respectively. My experience includes creating ER diagrams and using Rational Rose for data modeling and visualization, aiding in the design and understanding of complex data structures.