A professional Data Engineer currently working as a Data Engineer at Cognizant. I have 3+ years of experience in building, monitoring, supporting scalable and optimized data pipelines using various big data frameworks like Spark (Spark Core , Spark SQL), Hadoop, Hive, Pyspark, SQL, and cloud technology like AZURE and its data services like Data factory, Databricks, Delta Lake, Azure Data Lake Storage, Key-Vault, Synapse, etc. to build scalable ETL pipelines, enhance data quality, reducing project cost around 20%. A fervent advocate for transforming raw data into actionable insights. Technical Skills :- ➡️Programming Languages : SQL | Python | Spark-SQL ➡️Big Data Technologies: Apache Spark (PySpark) | Hadoop| Hive | HDFS | YARN ➡️Transactional Database & Data Warehousing: MySQL | Teradata ➡️Cloud Platforms: Azure | AWS ➡️Azure Data Services: Data Factory | Databricks | Azure Storage (Blob, ADLS Gen2) | Synapse Analytics | Delta Lake | Key Vault | SQL Database ➡️Version Control : GIT, GitHub ➡️Methodologies: Agile | Scrum | Jira ➡️Workflow Management : Autosys | Teradata Viewpoint ➡️DevOps : CI/CD | Jenkins ➡️Other: Relational Database Management Systems (RDBMS) | Data Modelling | Batch Processing | ETL Processes | Linux/Unix 🟢Certifications :- Azure Data Engineer-Associate | Azure Fundamentals Certified | AWS Certified Cloud Practitioner Building on belief that everything is possible with Learning, forgetting the past and focusing on the present to make Digital Future.