Git, Apache Spark, Databricks, Sql, Python, AWS, dbt

Agile and DevOps practices, GCP Cloud Composer, GCP Dataflow, GCP data engineering, Shell scripting or Python, GCP BigQuery, Relational databases RDBMS, Advanced SQL PLSQL scripting, Data processing and workflow orchestration, GCP Dataform

monte carlo , snowflake , Sql, ELT, Git, Azure, Python, Etl, Atlan, dbt, CI/CD, Fivetran, Immuta

Numpy, Pandas, Tableau, Sql, Python

Pyspark, Data Modeling, ELT, Cloud Storage, Numpy, Docker, Terraform, Python, BigQuery, Sql, Jenkins, Pandas, Spark, Kubernetes, Etl, GCP Core Services, Infrastructure as Code, Cloud Dataflow, Real-time streaming architectures, CI CD, Pub Sub, Cloud Run, GitHub Actions, API integrations, Cloud Functions, Cloud Dataproc, Cloud Composer Airflow

Version control (Git), Performance Tuning, Sql, Azure Data Factory, MySQL, Plsql, Rest Apis, Query Optimization, Data migration techniques, Data quality evaluation, Stored procedures, Azure Data Lake Storage, Modern data architectures, Data integration techniques, Indexing, CI/CD practices

Pyspark, Kafka, Sql, Jenkins, Gcp, Spark, Gitlab, Databricks, Azure, Python, AWS, DataOps, dbt, CI/CD

Power Bi, Pyspark, Azure Databricks, Azure Sql, Sql, Azure Data Factory, Azure Synapse Analytics, Spark, Python, Infrastructure as Code, Lakehouse Data Warehouse, DevOps practices, Medallion Architecture patterns, CI CD, Microsoft Purview, Data Lake technologies, Microsoft Fabric

snowflake , Aws Redshift, Power Bi, Data Warehousing, Tableau, Sql, Apache Airflow, Azure Data Factory, Azure Synapse Analytics, Apache Kafka, Databricks, Apache Iceberg, pipeline development, Google BigQuery, Looker, CI/CD pipelines, dbt, Delta Lake, Azure Event Hubs, Microsoft Fabric, AWS Kinesis, cloud-native data architecture, Databricks Workflows

snowflake , Azure Data Factory, Sql, Python, ETL Pipelines