Designs and builds scalable data pipelines using Hadoop, Spark, Kafka, and distributed systems for enterprise data workflows.

Analyzes business data, generates insights, builds dashboards, and supports decision-making using analytical and visualization tools.

Builds Spark streaming and batch applications using RDDs, DataFrames, and MLlib for high-performance analytics.

Manages Hadoop clusters, configures HDFS, monitors performance, and ensures reliability of distributed big-data systems.

Builds predictive models, applies machine learning, and works with large datasets to solve business problems.

Designs streaming architectures using Kafka, Flink, or Spark Streaming for real-time analytics and event processing.

Builds and maintains ETL workflows, handles data cleaning, transformation, and ensures high-quality structured datasets.

Designs large-scale data architectures, storage models, and enterprise data strategies using modern big-data platforms.

Develops ML models and integrates them into big-data environments using Spark MLlib and scalable pipelines.

Secures large datasets, ensures data governance, compliance, privacy, and risk-free big-data operations.