1 to 25 of 989 Remote Metadata Jobs

Azure, GCP) and associated managed services Experience with data modeling frameworks (e.g., star schema, snowflake schema) Knowledge of data governance principles, data cataloging, and metadata management Ability to work with version control tools (e.g., Git, SVN) and CI/CD pipelines Experience with containerization and orchestration technologies (e.g., Docker, Kubernetes More ❯

Design and implement robust ETL processes to integrate data from various sources into the data warehouse and big data platforms. Oversee the management of metadata, master data, and data lineage across systems. Ensure data consistency, accuracy, and availability for business users. Performance Optimization: Monitor and optimize the performance of data More ❯

Design and implement robust ETL processes to integrate data from various sources into the data warehouse and big data platforms. Oversee the management of metadata, master data, and data lineage across systems. Ensure data consistency, accuracy, and availability for business users. Performance Optimization: Monitor and optimize the performance of data More ❯

on Microsoft Azure. Unity Catalog Mastery: In-depth knowledge of setting up, configuring, and utilizing Unity Catalog for robust data governance, access control, and metadata management in a Databricks environment. Databricks Proficiency: Demonstrated ability to optimize and tune Databricks notebooks and workflows to maximize performance and efficiency. Experience with performance More ❯

on Microsoft Azure. Unity Catalog Mastery: In-depth knowledge of setting up, configuring, and utilizing Unity Catalog for robust data governance, access control, and metadata management in a Databricks environment. Databricks Proficiency: Demonstrated ability to optimize and tune Databricks notebooks and workflows to maximize performance and efficiency. Experience with performance More ❯

Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for pipeline development. Deep understanding of data architecture, dimensional modelling, and metadata management. Experience with cloud platforms (AWS, GCP, or Azure). Familiarity with version control, CI/CD , and Infrastructure-as-Code (Terraform or similar). More ❯

Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for pipeline development. Deep understanding of data architecture, dimensional modelling, and metadata management. Experience with cloud platforms (AWS, GCP, or Azure). Familiarity with version control, CI/CD , and Infrastructure-as-Code (Terraform or similar). More ❯

Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for pipeline development. Deep understanding of data architecture, dimensional modelling, and metadata management. Experience with cloud platforms (AWS, GCP, or Azure). Familiarity with version control, CI/CD , and Infrastructure-as-Code (Terraform or similar). More ❯

Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for pipeline development. Deep understanding of data architecture, dimensional modelling, and metadata management. Experience with cloud platforms (AWS, GCP, or Azure). Familiarity with version control, CI/CD , and Infrastructure-as-Code (Terraform or similar). More ❯

Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for pipeline development. Deep understanding of data architecture, dimensional modelling, and metadata management. Experience with cloud platforms (AWS, GCP, or Azure). Familiarity with version control, CI/CD , and Infrastructure-as-Code (Terraform or similar). More ❯

Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for pipeline development. Deep understanding of data architecture, dimensional modelling, and metadata management. Experience with cloud platforms (AWS, GCP, or Azure). Familiarity with version control, CI/CD , and Infrastructure-as-Code (Terraform or similar). More ❯

Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for pipeline development. Deep understanding of data architecture, dimensional modelling, and metadata management. Experience with cloud platforms (AWS, GCP, or Azure). Familiarity with version control, CI/CD , and Infrastructure-as-Code (Terraform or similar). More ❯

Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for pipeline development. Deep understanding of data architecture, dimensional modelling, and metadata management. Experience with cloud platforms (AWS, GCP, or Azure). Familiarity with version control, CI/CD , and Infrastructure-as-Code (Terraform or similar). More ❯

technologies such as BigQuery, Dataflow, Informatica, or IBM DataStage, supporting real-time and batch processing. Governance & Data Quality Management: Establish data governance frameworks, including metadata management and quality assurance, using platforms like Unity Catalog, Alation, Profisee, or DQ Pro. Strategic Advisory & Stakeholder Engagement: Partner with executive stakeholders (e.g., CDOs, CIOs More ❯

analytics. ETL/ELT pipeline development and optimisation to support large-scale data processing. Data integration across structured and unstructured sources, ensuring high availability. Metadata management and governance to maintain data quality and lineage. Deep expertise in Microsoft Azure cloud services, particularly for data analytics and engineering Databricks, including Delta More ❯

strategy pillars across people, processes and technology Knowledge and understanding of Data Management principles, including Data Governance, Data Quality, Master and Reference Data Management, Metadata Management, Security and Compliance Strong experience in Data Warehouse methodologies Strong experience in SQL Good understanding of Azure infrastructure (Subscriptions/Resource Groups, Virtual Networks More ❯

will provide expert guidance and advisory services to clients on a wide range of data management topics, including data governance frameworks, data quality policies, metadata management strategies, and master data management (MDM) solutions. You will provide strategic direction and leadership in Data Management, providing strategic and implementation consultancy in areas More ❯

and integration models Develop strategies for implementing a data warehouse, data lake, or hybrid model based on institutional needs Define and promote data standards, metadata management, and governance principles Collaborate with stakeholders across IT, Institutional Research, Enrollment, Finance, and Academic Affairs to understand reporting and analytics needs Partner with vendors More ❯

to streamline user authentication and improve security across cloud and on-premise applications. Proficient in data analysis, data lineage, data profiling, master data management, metadata management, ETL/ELT, data warehousing, data lake, data lakehouse, data governance, Big Data, AI/ML, reporting and data visualisation. Knowledge of IT infrastructure More ❯

to streamline user authentication and improve security across cloud and on-premise applications. Proficient in data analysis, data lineage, data profiling, master data management, metadata management, ETL/ELT, data warehousing, data lake, data lakehouse, data governance, Big Data, AI/ML, reporting and data visualisation. Knowledge of IT infrastructure More ❯

Platform. Knowledge of Microsoft D365 Finance & Operations and Customer Experience modules. Familiarity with Fabric, Azure Synapse, and data management practices including governance, quality, and metadata management (MS Purview). Relevant Microsoft certifications such as PL-300 (Power BI Data Analyst Associate) or DP-600 (Fabric Analytics Engineer Associate) are a More ❯

Platform. Knowledge of Microsoft D365 Finance & Operations and Customer Experience modules. Familiarity with Fabric, Azure Synapse, and data management practices including governance, quality, and metadata management (MS Purview). Relevant Microsoft certifications such as PL-300 (Power BI Data Analyst Associate) or DP-600 (Fabric Analytics Engineer Associate) are a More ❯

analytics. ETL/ELT pipeline development and optimisation to support large-scale data processing. Data integration across structured and unstructured sources, ensuring high availability. Metadata management and governance to maintain data quality and lineage. Deep expertise in Microsoft Azure cloud services, particularly for data analytics and engineering Databricks, including Delta More ❯

Platform. Knowledge of Microsoft D365 Finance & Operations and Customer Experience modules. Familiarity with Fabric, Azure Synapse, and data management practices including governance, quality, and metadata management (MS Purview). Relevant Microsoft certifications such as PL-300 (Power BI Data Analyst Associate) or DP-600 (Fabric Analytics Engineer Associate) are a More ❯

Platform. Knowledge of Microsoft D365 Finance & Operations and Customer Experience modules. Familiarity with Fabric, Azure Synapse, and data management practices including governance, quality, and metadata management (MS Purview). Relevant Microsoft certifications such as PL-300 (Power BI Data Analyst Associate) or DP-600 (Fabric Analytics Engineer Associate) are a More ❯