Bhavesh Sharma
Data Engineer at Carelon | Ex Coforge
- Role
- Azure Data Engineer at Coforge
- Location
- Gurugram, HR, IN
- LinkedIn followers
- 500 followers
About Bhavesh Sharma
Dynamic and results-oriented Cloud Data Engineer with experience in designing and developing efficient ETL processes and robust data pipelines. Proficient in optimizing data workflows to enhance performance and reliability. Strong expertise in Azure Data Factory (ADF), PySpark,Sql and Databricks for scalable data processing.Skilled in leveraging cloud services from Azure and AWS to deliver seamless data solutions. Adept at collaborating with cross-functional teams to drive data-driven decision-making and improve operational efficiencies. Committed to continuous learning and staying updated with the latest industry trends.Email- B••••••••@gmail.com
Experience
Azure Data Engineer
Aug 2022 — Present · Noida, IN
As a Data Engineer at Coforge, I spearheaded the development and implementation of a comprehensive data integration and analysis platform leveraging Azure technologies, Pyspark, Azure Data Factory (ADF), Azure Synapse Analytics, and SQL. Here\'s how I contributed to the project:Data Collection & Integration: OrchestratedAzure Data Factory (ADF) pipelines to collect data from various sources, including customer interactions and service logs. Utilized CSV and Parquet formats for efficient data storage and processing.• Data Storage & Management: Optimized database schemas in Azure Synapse Analytics to ensure efficient storage and maintain data quality and integrity. Utilized SQL for database management tasks and migration of existing data.ETL Processes: Designed and implemented ETL workflows using Pyspark within Azure Data bricks to clean, transform, and prepare data for analysis. Leveraged the power of Pyspark for processing large volumes of data in parallel.Big Data Technologies: Utilized Pyspark andSQL for processing and analyzing large datasets efficiently within Azure Data bricks. Leveraged the scalability and performance capabilities of Pyspark to handle Big Data workloads.NoSQL Databases: Integrated NoSQLdatabases such as MongoDB or Cassandra within Azure Synapse Analytics for handling unstructured data types.Distributed Systems: Designed fault-tolerant architectures within Azure Synapse Analytics to handle high data volume and ensure reliability and availability of data processing pipelines.• Streaming Data: Utilized Azure Stream Analytics for real-time processing of streaming data from sources like Apache Kafka or Amazon Kinesis, enabling timely insights and decision-making.
Education
IP College
Bachelor of computer applications
2016 — 2019
GL Bajaj Institute of Technology and Management
Master of Computer Applications - MCA
2019 — 2021
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