I will do big data engineering with pyspark, kafka, airflow, AWS etl and mongodb

I work with industry-leading big data tools including Hadoop, Spark, Kafka, Hive, and PySpark. These technologies allow me to design scalable data engineering solutions, build efficient data pipelines, and process large datasets for analytics.

Yes, I specialize in building complete big data pipelines using Hadoop and Spark. From data ingestion to transformation and storage, I create reliable ETL workflows tailored to your business needs.

Absolutely. I develop real-time data streaming pipelines using Kafka, enabling you to process and analyze streaming data efficiently for use cases like monitoring, analytics, and event-driven systems.

I offer a wide range of data engineering services including ETL development, big data processing, Hadoop cluster setup, Spark optimization, Kafka integration, and data analytics solutions.

es, I can analyze and optimize your existing Hadoop or Spark infrastructure to improve performance, reduce processing time, and ensure efficient resource utilization.

Yes, PySpark is one of my core skills. I use it extensively for building scalable data engineering workflows, performing data transformations, and handling large-scale big data processing tasks.

I follow best practices in data engineering such as validation checks, logging, error handling, and testing to ensure high data quality and reliable ETL pipelines using tools like Spark, Hadoop, and Kafka.