Data Architecture, Apache Spark, Data Warehousing, Technical Leadership, Python, Sql, Cloud Data Engineering, Databricks on AWS, Lakehouse Architecture, CI CD DevOps Practices

containerization , Sql, Incident Management, Data Warehousing, Data Architecture, Data Quality, Data Governance, Python, Orchestration, Transformation, Cloud data platforms, Monitoring, Deployment automation, Infrastructure-as-Code, GitOps

Data Warehousing, Sql, Databricks, ELT, Etl, Python, Devops, Scala, Spark, Databricks SQL, Unity Catalog, Delta Lake

Dimensional Modeling, Sql, Python, Sdlc, Aws, IT

Scala, Sql, ELT, Devops, Spark, Databricks, Data Warehousing, Python, Etl, Databricks SQL, Unity Catalog, Delta Lake

Sql, Kinesis, Kafka, AWS, Cloudformation, Python, Azure, Gcp, Terraform, Spark, dbt, Airflow, Prefect, Dagster, Pub Sub, DataOps practices

snowflake , Python, Sql, Apache Airflow, Azure Data Factory, Azure Synapse, Hl7, 837, 835, X12, dbt, FHIR

Spark, AWS, Azure, Scala, Google Cloud Platform, Flink, NoSQL databases, Spark Structured Streaming

Dynamodb, Databricks, Sql, Apache Airflow, CDK, AWS Glue, Apache Spark, Kinesis, Postgres, Kafka, MLops, AWS, Cassandra, Nosql, Python, Terraform, MongoDB, MLflow, Flink

Cassandra, PostgreSQL, Distributed Systems, MySQL, AWS, Java, Rust, Dynamodb, Gcp, MongoDB, Azure, data pipelines, streaming systems, Benchmarking, Go, Data Storage, Capacity Planning, retrieval, advanced algorithms, SQL databases, observability, ClickHouse, NoSQL databases, event-driven architectures, scalable data structures, Performance Analysis