Data Quality, Azure Data Factory, Pyspark, Data Warehousing, Data Governance, Databricks, Data Modeling, Etl, ELT, Microsoft Fabric

snowflake , operational support , Metadata Management, Sql, ELT, Data Modeling, Data Governance, Etl, Data Quality, Python, RAG pipelines, vector databases, AI LLM-enabled data architectures

snowflake , Google Cloud Platform, Data Quality, Data Modeling, Sql, ELT, Apache Airflow, Azure Data Factory, Databricks, Azure, Python, AWS, Etl, Microsoft Fabric

snowflake , Sql, ELT, Etl, Data Modeling, Data Governance, Python, Metadata Management, data quality controls

data curation , Devops, Gcp, Data Modeling, Azure, Python, Etl, AWS, AI tools, analytical workloads

Pyspark, Data Governance, Data Modeling, Azure Synapse, Encryption, Spark SQL, Data Warehousing, Sql, Git, Azure Data Factory, Purview, Key Vault, PII handling, Event Hubs, Notebooks, DevOps practices, Dataflows Gen2, ADLS Gen2, Semantic layer design, rbac, Lakehouse, CI CD pipelines, Delta Lake, Microsoft Fabric, Azure Data Services

Scipy, AWS Athena, Apache Airflow, Devops, Pandas, Numpy, Gcp, Spark, Python, Google Datalab, Apache Druid, scikit-learn, MLlib, Google BigQuery, Imply, Zeppelin, Jupyter

Metadata Management, Sql, ELT, Apache Airflow, Data Quality, Data Warehousing, Python, Etl, Oracle-to-GCP data migration, audit frameworks, Reconciliation, GCP IAM, Google BigQuery, Pub Sub, watermarking, Oracle databases, Google Cloud Dataflow, Data Validation, DAG Factory, Google Cloud Composer

Database Design, Data Governance, Data Modeling, Snowflake Data Warehouse, ETL processes, data integration techniques, data quality best practices, cloud platforms and services