I am a meticulous and resourceful Sr Data Engineer with around 12 years of experience in the field. Throughout my career, I have demonstrated expertise in managing, leading, and mentoring teams while designing and executing solutions for complex business problems. My skill set encompasses large-scale data warehousing, real-time analytics, and reporting solutions, as well as building highly scalable, robust, and fault-tolerant systems both on the cloud and on-premises.I have provided clients with data analytics solutions and support, helping them optimize their data processes and achieve actionable insights.My extensive experience includes mentoring, managing, architecting, designing, and delivering data warehousing, data integration, migration, and conversion projects.As a Lead Data Engineer at CPC, I played a crucial role in designing efficient solutions, developing process flows, and performing transformations for data pipelines. I was responsible for maintaining data quality and ensuring synchronization across different systems.During my tenure at Ernst & Young (EY), I led a team and contributed significantly to the Data Ingestion & Migration Process. I designed and developed data warehouses and integration solutions, including migration strategies to Azure, AWS, GCP, and large-scale customization projects.As a Microsoft Business Intelligence Consultant at L&G Technologies, I contributed to the creation of functional requirement specifications, Data Ingestion & Migration Processes.I am passionate about leveraging technology and data for business growth, I excel in process improvements, automation, optimizing data delivery, and scalable infrastructure setups. With keen data analysis skills, I drive data-driven decision-making and collaborate effectively with cross-functional teams. With a proven track record of successful projects, strong technical expertise, and leadership abilities, I am poised to make a significant impact in driving business innovation and growth.Technology Stack: Hadoop, HDFS, Talend, Hive, HDFS, T-SQL, Python, Spark, REST APIs, Confluence, JIRA, Bit Bucket, CI/CD, Python, Airflow, MS Office, Erwin, SSIS, ADF, SSMA, Unix, Mainframe, Databricks, SQL Server, Data Lake, Docker, Kubernetes, Power BI, Guidewire, Control-M, SQL Server, SSRS, DevOps, Datahub, InfoCenter, SAP BODS, JAVA, Big Query, MS SQL, MongoDB, Redshift, Neo4j, PostgreSQL, Azure SQL, Snowflake, Oracle, Cosmos DB, Azure synapse, GCP, Azure, and AWS, GitHub