Metadata Management, Databricks, Python, Data lineage techniques, Master data management, Data modeling methodologies, Big Data storage architecture

Data governance and quality assurance practices, Databricks Unified Data Analytics Platform, Building and managing scalable data pipelines and workflows, Data integration and ETL processes, Cloud-based data storage and processing solutions

Data Quality, Metadata Management, Data Governance, Python, Sql, workflow orchestration tools, ETL ELT frameworks, AWS cloud platforms, data lake architecture

Data Modeling, Pyspark, Sql, Git, Azure Data Factory, Databricks, Data Warehousing, Azure DevOps, GitHub Actions, Synapse Analytics, Delta Lake, Microsoft Fabric

graph databases , object storage , S3, Emr, Data Modeling, Redshift, Sql, Lambda, AWS, Etl, column-family databases, data stores, key-value stores, non-relational databases

data engineering , snowflake , Pyspark, Tableau, Excel, Data Governance, Python, AWS, Cloud Architecture, Sql, Data Quality, Gcp, Powerbi, Databricks, Api, Azure, data integration techniques, Data Operations, Data Technology Architecture, Data Harmonization, dbt, cloud-based databases, Synapse, Data Cataloging, Master Data Management

amazon dynamodb , Apache Hadoop, Aws Lambda, Agile Methodologies, Etl Development, PostgreSQL, Data Warehousing, Apache Spark, Data Modeling, Jira, Sql, Devops, Amazon Redshift, MySQL, Scrum, Python, AWS, Amazon QuickSight, Amazon EMR Serverless, data ingestion

data streaming , Github, Apis, Data Modeling, PostgreSQL, Performance Tuning, Pyspark, Pl Sql, Autosys, Db Design, Sql, Unix Shell Scripting, Agile Software Development, Apache Kafka, Oracle, Python, AWS, Airflow, NoSQL databases, Data Bricks