Rakshit Kondla
Data Engineer @John Deere
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WORK HISTORY
Data Engineer @John Deere
Moline, IL, US
Designed and implemented a robust data pipeline using Amazon Kinesis for real-time streaming data ingestion, enabling seamless processing of telematics and alerts data.Developed and optimized ETL workflows in Databricks using PySpark to transform and load streaming data into EDL tables, ensuring high performance and scalability.Integrated Databricks with AWS Glue to catalog and manage metadata, improving discoverability and governance for downstream processes.Built Spark-based data transformation jobs to process telematics, alerts, and streaming data, ensuring accurate partitioning and writing to EDL tables.Automated data ingestion pipelines to move processed data from Databricks to AWS S3, enabling efficient storage and accessibility for analytical purposes.Created Python-based Databricks notebooks to process and convert data into CSV files, later importing them into Aurora PostgreSQL for structured reporting and analysis.Leveraged RDS Connectors to streamline data integration between Aurora PostgreSQL and internal dashboards, enhancing accessibility for end-users.Implemented data visualization and reporting using Dash Plotly, delivering actionable insights through an internal PIN MD tool integrated with Okta for secure access.Improved fault tolerance and monitoring of data pipelines using AWS CloudWatch, ensuring reliable processing of real-time telematics and measures data.Collaborated with cross-functional teams to integrate Okta-based authentication into internal tools, ensuring secure access to dashboards and reports.Orchestrated and managed data processing workflows with Databricks, leveraging its SQL Connector for seamless integration with downstream reporting applications.Designed and implemented EDL (Enterprise Data Lake) tables to store streaming data, improving accessibility for downstream analytics and reporting.
EDUCATION
University of North Texas
Master's degree
ABOUT RAKSHIT KONDLA
Experienced Data Engineer with a strong background in building scalable and robust data pipelines. Skilled in designing and implementing complex data architectures that optimize data processing, storage, and retrieval. Proficient in programming languages such as Python and SQL, with expertise in big data technologies such as Hadoop, Spark, and Kafka. Passionate about leveraging data to drive business insights and improve decision-making. Seeking opportunities to apply my skills and knowledge in a dynamic and collaborative environment.\"
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