Data Governance, ETL process design, data storage solutions, data integration techniques, distributed computing environments, cloud-based data platforms, data quality best practices, Microsoft Azure Databricks, data pipeline architecture

Spark, Emr, Dynamodb, Lambda, Pyspark, Deduplication, Terraform, Scala, PostgreSQL, S3, AWS, Python, Advanced Sql, resilient pipeline patterns, AWS Sagemaker, Glue, Type 2 Dimensions, Medallion Architecture, Lakehouse, Idempotency, Incremental historical processing, late-arriving data handling, AWS data services, Step Functions, CDC Merge processing, Aurora

Pyspark, Apache Spark, Kafka, Emr, Redshift, Sql, ELT, Lambda, Kinesis, Data Warehouse Architecture, Data Lake, Python, Aws S3, Etl, Airflow, CI CD, Lake Formation, pipeline development, Glue, AWS Security, Athena, Real-Time Data Processing, Cloud Optimization

data warehouses , Machine Learning, Pyspark, Sql, ELT, Data Quality, Git, Databricks, Python, Etl, Data Lakes, Cloud-based Data Platforms, Ai, Delta Lake

Sql, AWS, Aws Redshift, Dynamodb, Python, PostgreSQL, MongoDB, AWS Batch, ETL processes, data pipeline architecture

Powerbi, Sql, Jira, Azure Databricks, Gcp, Azure DevOps, Azure Logic Apps, Shell scripting, Azure Data Factory, Pyspark, Azure Functions, Python, Apache Kafka, Synapse Fabric, Azure CLI, Azure Networking, Data Modelling Architecture, ETL pipeline design, Databricks online table, Logging and Monitoring using Azure Databricks services, Azure cloud data services technologies, Unity Catalog, Microsoft EntraID, Delta live table, Azure API service, AWS cloud services knowledge

Data Warehousing, Designing, Snowflake Platforms, SQL Optimization, Cloud based Architectures