• Over 9+ years of experience in Information Technology which includes Hands on experience in Hadoop ecosystem including Spark, Kafka, HBase, MapReduce, Python, Scala, Pig, Impala, Sqoop, Oozie, Flume, Storm, big data technologies and worked on Spark SQL, Spark Streaming and using Core Spark API to explore Spark features to build data pipelines.• Experience in building bigdata solutions using Lambda Architecture using Cloudera distribution of Hadoop, Twitter Storm, Trident, MapReduce, Cascading, HIVE, PIG and Sqoop.• Strong Knowledge and experience on implementing Big Data in Amazon Elastic MapReduce (Amazon EMR) for processing, managing Hadoop framework dynamically scalable Amazon EC2 instances, Lambda, SNS, SQS, AWS Glue, S3, RDS and Redshift.• end-to-end implementation project experience on data processing pipeline using Hadoop (CDP) ecosystem, Data Lake, and Data Warehouse.• Strong experience with AWS Cloud on data integration with Databricks, Apache Spark, Airflow, EMR, Glue, Kafka, Kinesis and Lambda in S3, Redshift, RDS, MongoDB/DynamoDB ecosystems.• Responsible for the design and development of data related solutions (databases, ETL systems, code, scripts, data models, reports, documentation) and supporting various products. Extensive hands-on experience developing database queries, ETL, performance tuning and database unit tests in a relational database environment.• Having experience in developing a data pipeline using Kafka to store data into HDFS and Experience in building Real-time Data Pipelines with Kafka Connect and Spark Streaming and developing end to end data processing pipelines that begin with receiving data using distributed messaging systems Kafka for persisting data into Hive.• Experienced in development methodologies like Agile/Scrum.• Excellent Experience in Designing, Developing, Documenting, Testing of ETL jobs and mappings in Server and Parallel jobs using Data Stage to populate tables in Data Warehouse and Data marts.• Expertise in transforming business requirements into analytical models, designing algorithms, building models, developing Data Mining, Data Acquisition, Data Preparation, Data Manipulation, Feature Engineering, Machine Learning Algorithms, Validation and Visualization and reporting solutions that scales across massive volume of structured and unstructured Data.• Strong knowledge in working with ETL methods for data extraction, transformation, and loading in corporate- wide ETL Solutions and Data Warehouse tools for reporting and data analysiss.