Data Quality (DQ) rules, Metadata Management, Unix, Databricks, Python, Data lineage techniques, Master data management, Data modeling methodologies, Big Data storage architecture

Workflows, Apis, Cloudformation, Pyspark, Sql, Devops, MLops, Terraform, Spark, Databricks, Azure, Python, AWS, Databricks Lakehouse, dbt

Scala, Apache Spark, Data Modeling, Sql, ELT, Data Warehousing, Etl, Google BigQuery, Data quality monitoring, Cloud-based data platforms, Production Support, Big Data Distributed Processing, Observability

snowflake , Apache Spark, Kafka, Sql, ELT, Apache Airflow, Spark Streaming, Gcp, Docker, Azure, Python, Kubernetes, AWS, Etl, dbt

BigQuery, Scala, Apache Spark, Kafka, Dataproc, Jenkins, Git, Hive, Gcp, Etl, workflow orchestration tools, CI CD, Pub Sub, GCS

snowflake , BigQuery, AWS Glue, Redshift, Sql, Data Integration, Azure Sql, ELT, Azure Data Factory, Gcp, Data Architecture, Databricks, Azure, Python, AWS, Etl, Airflow, Cloud Data Platforms

Unix, Oracle Sql, Pyspark, Data Warehousing, Kafka, Pl Sql, Data Modeling, shell scripting, Python, Spark SQL, Apis, SQL Server, Sql, Azure Data Factory, Linux, Restful Services, Databricks, Event Hubs, Structured Streaming, monitoring practices, Lakehouse medallion architecture, data quality testing, ADLS Gen2, Auto Loader, Unity Catalog, Delta Lake

snowflake , Java, Scala, Pyspark, Apache Spark, Sql, Gcp, Terraform, Docker, Databricks, Azure, Python, Kubernetes, AWS, Airflow, Deequ, Great Expectations, Prefect

Java, BigQuery, Hive, Spark, Python, Linux systems