Akhil Niranjan

• Around 5 years of experience in the software industry, including 5 years of experience in Azure cloud services, and 4 years of experience in Data warehouse. • Experience in Azure Cloud, Azure Data Factory, Azure Data Lake storage, Azure Synapse Analytics, Azure Analytical services, Azure Cosmos NOSQL DB, and Data bricks. • Extensive using Azure activities like Get Metadata, Azure Function, Data Flow, Lookup, webHook, Copy data, and ForEach. • Implemented event driven messages using Azure EventHub. • Experience in building data pipelines, and computing large volumes of data using Azure Data Factory. • Strong knowledge of Extraction Transformation and Loading (ETL) processes using UNIX shell scripting, SQL Loader and handled metadata using messages for data analysis. • Used JIRA as an agile tool to keep track of the tickets that were worked on using the Agile methodology. • Experienced in working in SDLC, Agile and Waterfall Methodologies. • Hands on Experience in using Visualization tools like Tableau, Power BI. • Collaborated with cross-functional teams to design and implement effective data solutions using Azure Purview and other Azure services, fostering data-driven culture and improving overall data management. • Data Mesh, utilizing its capabilities to streamline data governance, integration, and domain-oriented data management. • Experience in developing, supporting, and maintenance for the ETL (Extract, Transform, and Load) processes using Informatica. • Hands on experience on Hadoop, HDFS, Hive, Sqoop, Spark, YARN, Kafka, PySpark, Airflow, Snowflake, SQL, Python. • Experience in developing very complex mappings, reusable transformations, sessions, and workflows using the Informatica ETL tool to extract data from various sources and load it into targets. • Proficiency in multiple databases like MongoDB, Cassandra, MySQL, ORACLE, and MS SQL Server. • Experience in Developing Spark applications using Spark - SQL in Databricks for data extraction, transformation, and aggregation from multiple file formats for analyzing and transforming the data to uncover insights into customer usage patterns. • Used various file formats like Parquet, CSV, JSON and for loading data, parsing, gathering, and performing transformations. • Extensive experience in working with Hortonworks Hadoop distribution