Pyspark, Scala, Data Governance, Sql, Azure Data Lake, Profisee, Python, Big Data Architecture, Azure Purview, Databricks GenAI, Batch streaming, Unity Catalog, Delta Lake, Microsoft Azure Databricks

architectural patterns , Data Modeling, Data Governance, metadata schemas, controlled vocabularies, FAIR principles, metadata lineage, FAIR assessments, reuse readiness, metadata architecture, Reference Data, semantic standards, domain model alignment, interoperability coverage, metadata completeness

data warehouses , , Data Governance, Data Quality, ETL Processes, data models, Data Storage

Integration, S3, Aws Services, Emr, Kafka, Python, Sqs, Data Warehousing Concepts, Apis, Data Modeling, Airflow, Event Bridge, Glue, AppFlow

snowflake , SQL Server, data architecture principles, data modeling techniques

Data Governance, Databricks, Sql, Data Factory, Ab Initio, Pyspark, Alteryx, Talend, Python, Informatica, Azure, Azure DevOps, GitHub Actions, Airflow, CI-CD

data engineering , snowflake , Cassandra, Kafka, Edw, AWS, Redis, Gcp, Spark, Data Governance, Databricks, MongoDB, Azure, Big Data engineering, cloud-based architectures, ML platforms, Sagemaker, data lakes, ML and MLOps, streaming big data, mlflow, analytical data platforms, Dataiku, Transactional databases, VertexAI, data mesh

.NET, data products , Databricks, Sql, SQL Server, Data Modeling, Java, Machine Learning, AWS, Data Warehousing, Python, Azure, Microservice Architecture, Microsoft Fabric, data mesh, Azure Data Services, data lakes

snowflake , Data Security, Sql, Data Modeling, Python, Data ingestion

Spark, S3, Bitbucket, Emr, AI ML, Lambda, Terraform, Jenkins, Dimensional Data Vault 2.0, Lake Formation, 3NF, Streaming Kinesis, infrastructure as code, MSK, Warehouse Redshift, AWS data services, CI CD, data modeling techniques, SageMaker Unified Studio, Storage Lakehouse, AWS CDK, Processing Glue