Platform engineering, analytics infrastructure, and reliability operations.
Owned and operated petabyte-scale, real-time data processing systems using Spark Structured Streaming, Kafka, and Apache Druid.
Stack: AWS (S3, Glue, Redshift, EMR, Kinesis, MSK), PySpark, Scala, Jenkins, Terraform, DBT, Airflow
Architected scalable GCP data platforms; led advanced analytics and ML workflows with Vertex AI, Spark, and Snowflake.
Stack: GCP (BigQuery, Dataflow, Composer, Dataproc, GCS), Python, Spark, dbt, Snowflake, Kubernetes
Migrated ETL workflows to Azure Data Factory and optimized large-scale data pipelines using Azure Databricks.
Stack: Azure (ADF, Databricks, Blob Storage, Synapse), Scala, PySpark, SQL, Tableau, Power BI
Designed end-to-end backend and cloud-native data ingestion workflows on Oracle Cloud Infrastructure.
Stack: OCI, Python, Apache Spark, REST APIs, React, TypeScript
Engineered distributed systems and high-throughput ingestion pipelines within the Hadoop ecosystem.
Stack: Hadoop (Hive, Pig, HBase, MapReduce), Spark (Scala), Python, Django, Spring Boot, RabbitMQ
Built distributed backend systems and optimized ETL pipelines for large-scale data processing.
Stack: Apache NiFi, Hive, Spark, Django, Spring Boot, Go, PostGIS