snowflake , Java, BigQuery, Scala, Apache Spark, Kafka, Sql, Gcp, Databricks, Azure, Python, AWS, Flink, Iceberg, Delta Lake

data engineering , Machine Learning, Python, Sql, Continuous Integration, Distributed processing, Infrastructure-as-code, Workflow orchestration, Cloud data platform

Power Bi, Sql, Hive, Python, SAS, Unix Shell, Tableau, Spark, Oozie, ETL processes, Airflow

composer , Google Cloud Platform (GCP), BigQuery, Dimensional Modeling, Sql, Apache Airflow, Dataproc, DataFlow, Talend, Python, dbt, Infrastructure as Code, Slot and Reservation Management, Query Performance Tuning, Data Pipelines, Data ETL Architecture, Cost Optimization, Streaming and Near Real-time Architectures, Partitioning and Clustering Strategy, Data Quality Observability and Testing Frameworks, CI/CD for Data Workloads, ETL Engineering, Fivetran

monte carlo , Pyspark, AWS Glue, Data Warehouse, Sql, ELT, Jenkins, Git, Azure Data Factory, Gcp, Data Lake, Databricks, Azure, Python, Etl, AWS, Azure DevOps, Delta Lake, Great Expectations

Cloud Computing, Data Warehousing, Python, Sql, Etl

Software Development Lifecycle, Docker, Big Data, FastAPI, Restful Apis, Python, Kubernetes, NoSQL and document databases, CI/CD practices, Design and architecture of large distributed systems

Jenkins, Git, Liquibase, Cloudwatch, Gcp, Terraform, Python, Flyway, Memory allocation, Index strategies, Database observability metrics, SQL execution plans, Partitioning, Database Performance Optimization, Azure Monitor

data vault , Kafka, Data Modeling, Dimensional Modeling, Kinesis, Python, Apache Spark, Data Warehousing, Sql, Git, Apache Iceberg, Airflow, Infrastructure as Code, Monitoring solutions, Performance optimization, Streaming data processing, Flink, Workflow orchestration, Partitioning, Apache Hudi, Schema evolution, Delta Lake, Batch and real-time ETL/ELT pipelines, CI/CD, Data quality frameworks