Anand Babu Devarakonda

1. Big Data Analytics and Engineering: - 9+ years of overall IT experience with a focus on Big Data Analytics and development. - Experience in collecting, processing, and aggregating large amounts of streaming data using Kafka and Spark Streaming. - Deep hands-on experience with Python, PySpark, Scala programming languages, and SQL, PL/SQL scripting languages. - Experience in managing and analyzing massive datasets on multiple Hadoop frameworks like Cloudera and Hortonworks. 2. Cloud Data Engineering: - Experience as a Data Engineer responsible for data cleaning, data modeling, data migration, and ETL pipeline preparation for both cloud and on-premises platforms. - Worked in an AWS environment with services like Lambda, AWS RedShift, EMR, RDS, and EC2. - Migrated an existing on-premises application to AWS, utilizing services such as EC2 and S3 for data processing and storage. - Developed and implemented database solutions using Azure SQL Data Warehouse and Azure SQL Database. 3. Data Processing and Analysis: - Experience in designing Data Marts following Star Schema and Snowflake Schema Methodology. - Highly skilled in Business Intelligence tools like Tableau, PowerBI, and Snowflake for data validations. - Worked with various data formats such as JSON, Avro, Parquet, RC, and ORC, and compressions like Snappy and Gzip. - Excellent understanding of Hadoop architecture and various components such as HDFS, Job Tracker, Task Tracker, Name Node, Data Node, Resource Manager, and Node Manager. 4. Data Integration and Analytics: - Good understanding of Azure Big Data technologies like Azure Data Lake Analytics, Azure Data Lake Store, Azure Data Factory, Azure Databricks. - Experience in Spark-Scala programming, designing and developing applications in Spark using Python. - Worked in Kafka streaming environment for data processing, configurations, and reading/writing data from/to various databases. - Hands-on experience with data analytics services such as Athena, Glue Data Catalog & QuickSight, and working experience with Hive and HBase/MapRDB integration. 5. Azure Data Services and Analytics: - Demonstrated experience with various Azure data services such as Azure Data Lake Analytics, Azure Data Lake Store, Azure Data Factory, and Azure Databricks. - Proficient in leveraging these services to enable data processing, storage, and analytics capabilities in the cloud.