data engineering , Spark, Databricks, Data ingestion strategies, Partitioning, ADLS, Resource Allocation, Incremental loads, Schema evolution, Spark optimization techniques, Caching

data warehouses , Metadata Management, Scala, Sql, Data Quality, Spark, Etl Tools, Data Governance, Data lakes, NoSQL databases, Cloud data solutions implementation, Generative AI technologies, Streaming platforms, Data visualization tools, Data Cataloging, Data modeling techniques, Data architecture solutions

AWS AI Services, data integration methods and tools, Databricks Unified Data Analytics Platform, Snowflake Data Warehouse, database design principles, AI Data Solution Architecture, data modeling techniques

snowflake , Pyspark, Scala, Apache Spark, Azure, Google Cloud, Etl, AWS, Data Integration frameworks, DataFrames

Hadoop, Distributed Systems, Big Data Architect, AI Harness platforms, Temporal workflow orchestration, AWS Migration, cloud-native data engineering

Spark SQL, Storm, Flume, Kafka, Impala, Mapreduce, Pig, Apache Nifi, Rabbitmq, Hive, Gcp, Linux, Big Query, Hadoop v2, Airflow, HDFS, Data Proc, Cloud Composer, data fusion, dbt, Data Flow

Apache Spark, Advanced Sql, Python

snowflake , Sql, Emr, Yarn, Hadoop, Kafka, BigQuery, Etl, Hive, Gcp, ELT, Apache Airflow, Aws S3, Apache Spark, AWS, Python, Azure, Spark, Redshift, Apache Iceberg, EKS, Synapse, HDFS, Glue, Athena, K8S