Performance tuning and optimization of database systems, Oracle Database Architecture, Data modeling and database design principles, Cloud-based data solutions and architectures, Microsoft SQL Server Administration, Data governance and compliance standards

Pyspark, Kinesis, Terraform, Python, Emr, Pulumi, Apache Kafka, Databricks, DataFlow, Aws S3, Apache Iceberg, Pub Sub, High-Throughput Message Bus, Apache Atlas, Azure ADLS Gen2, Event Hubs, Apache Hudi, MCP Server Foundation, Multi-Cloud Enablement, Unity Catalog, Synapse, DataHub, Glue, Delta Lake, GCP BigQuery, Athena

bigtable , Java, BigQuery, PostgreSQL, Scala, Sql, Redis, Spark, Apache Kafka, MongoDB, DataFlow, Python, datastream, Airflow, Debezium, Pub Sub, CDC tools, dbt, GCS, GCP stack, Spanner

data engineering , Analytics Delivery, Graphql, Spark, Rest Apis, Data Architecture, Sql, Python, Event-driven design

Power Bi, Data Governance, Databricks, Encryption, Redshift, Sql, Python, IAM access controls, AWS architecture, Athena, Graph modeling

lifecycle management , Rabbitmq, Devops, Kafka, Angular, Node.js, Nosql, Mean Stack, REST, Couchdb, Influxdb, Microservices, Express, Graphql, Apis, MongoDB, observability frameworks, Security, distributed data platforms, platform governance, time-series databases, backend design, Service Bus, event-driven systems, data architectures, relational SQL, Messaging, Timescale

messaging platforms , lifecycle management , Rabbitmq, Kafka, Angular, Node.js, Nosql, Mean Stack, Couchdb, Influxdb, Express, MongoDB, Timescale, Security, cloud-native environments, DevOps practices, backend system design, platform governance, Service Bus, unstructured data systems, event-driven systems, data architectures, observability frameworks, GraphQL APIs, relational SQL, microservices architecture

Azure Data Lake (ADLS), Azure Databricks, Azure Data Factory, Azure Event Hub, Azure IoT Hub