51 to 75 of 587 Metadata Jobs

Unit Testing - Experience in writing unit tests for data pipelines. Data Architecture - Knowledge or experience in implementing, Kimball style Data Warehouse. Experience in building Metadata with Azure Purview or Data Lake Gen2. Data Quality - Experience in applying Data Quality rules within Azure Data Flow Activities. Data Transformation - Extensive hands-on More ❯

Unit Testing - Experience in writing unit tests for data pipelines. Data Architecture - Knowledge or experience in implementing, Kimball style Data Warehouse. Experience in building Metadata with Azure Purview or Data Lake Gen2. Data Quality - Experience in applying Data Quality rules within Azure Data Flow Activities. Data Transformation - Extensive hands-on More ❯

Unit Testing - Experience in writing unit tests for data pipelines. Data Architecture - Knowledge or experience in implementing, Kimball style Data Warehouse. Experience in building Metadata with Azure Purview or Data Lake Gen2. Data Quality - Experience in applying Data Quality rules within Azure Data Flow Activities. Data Transformation - Extensive hands-on More ❯

Responsibilities will include: Data Create and maintain robust and scalable data pipelines to ingest, process, and transform data from various sources, ensuring data and metadata quality, accuracy, and consistency. This will include working with large and complex datasets, such as census and international data. Responsibility for implementation of data governance More ❯

of ETL/ELT, data warehousing, and data mesh architectures. Familiarity with AI/ML concepts and their application in data analytics. Experience with metadata management, data lineage tracking, and data cataloging. Understanding of serverless data processing, event-driven architectures, and modern data stacks. More ❯

of ETL/ELT, data warehousing, and data mesh architectures. Familiarity with AI/ML concepts and their application in data analytics. Experience with metadata management, data lineage tracking, and data cataloging. Understanding of serverless data processing, event-driven architectures, and modern data stacks. More ❯

Dimensional modelling methods Implement automated, reusable and efficient batch data pipelines and streaming data pipelines Work closely with Governance and Quality teams to ensure metadata, catalogue, lineage and known solutions to data issues are optimised Work closely with other data specialists and technicians in the organisation, such as Actuarial and More ❯

Ensure data models align with organizational data architecture and governance standards. Optimize database structures for performance, scalability, and reliability. Document data models, relationships, and metadata for reference and maintenance. Work with development teams to implement data models in database systems. Conduct data analysis to ensure data quality and integrity. Support More ❯

Dimensional modelling methods Implement automated, reusable and efficient batch data pipelines and streaming data pipelines Work closely with Governance and Quality teams to ensure metadata, catalogue, lineage and known solutions to data issues are optimised Work closely with other data specialists and technicians in the organisation, such as Actuarial and More ❯

What You’ll Bring: Senior-level experience in data, analytics, or governance (financial services a plus) Strong knowledge of data governance, data quality, and metadata management Proficiency in Power BI, SQL, and Azure-based platforms (Synapse, Data Factory, Databricks) Familiarity with data regulations (GDPR, FCA) and SMCR environments Bonus points More ❯

What You'll Bring: Senior-level experience in data, analytics, or governance (financial services a plus) Strong knowledge of data governance, data quality, and metadata management Proficiency in Power BI, SQL, and Azure-based platforms (Synapse, Data Factory, Databricks) Familiarity with data regulations (GDPR, FCA) and SMCR environments Bonus points More ❯

Assist in reviewing data models and integration designs for adherence to established data architecture standards. Support the development and maintenance of data dictionaries and metadata repositories, including researching definitions, validating data elements, and documenting business rules. Participate in data governance initiatives, tracking action items and supporting the implementation of data More ❯

/ELT processes. Proven experience integrating new data sets into an established data platform and optimizing data storage and processing. In-depth knowledge of metadata management , self-serve data models , and data governance principles. Strong understanding of risk management frameworks , data controls, and ensuring compliance with industry regulations. Familiarity with More ❯

functional teams to understand data requirements and implement solutions that meet business needs. • Develop and maintain data catalogs within Databricks, ensuring accurate documentation and metadata management. • Optimize and troubleshoot existing ETL processes to improve efficiency, reliability, and performance. • Stay up-to-date with the latest Azure technologies and best practices More ❯

Lake, Azure Data Lake Storage Gen2, and data formats such asJSON and Parquet. Ability to design modular, reusable pipeline components with robusterror handling and metadata-driven architecture. Experience working with public datasets, government transparency data, or publishing workflows. Knowledge of data privacy and protection techniques, including PII handling,data masking More ❯

MDM solutions, with a deep understanding of both operational and technical aspects, including architecture. Proficiency in designing robust master data models and architecture , managing metadata , and optimizing the data lifecycle to ensure accuracy and consistency across systems. Solid experience with agile project management and change management , with the ability to More ❯

full life-cycle software development projects Demonstrated knowledge in enterprise data strategy, data governance practices, data stewardship principles, data architecture principles, data standards, and metadata management best practices Desired: Ability to convey technical information to non-technical individuals Ability to work in a dynamic and challenging environment Strong oral and More ❯

Extract, Transform, Load) processes. Design and implement data models to support business processes and data analysis. Enforce data quality standards, data security policies, and metadata management practices. Monitor and optimize data platform performance, ensuring scalability and reliability. Evaluate and recommend data technologies and tools to meet business needs. Collaborate within More ❯

refining processes and improving the agility and quality of delivery. Supporting the adoption and optimisation of tools such as Alation for data cataloguing and metadata management. Working closely with business and technical stakeholders to ensure our data models are of the highest quality and fit for purpose. What you'll More ❯

date and accurate documentation, including lineage, for all production solutions. Monitoring and optimising the performance of data warehouse systems. Managing data models, schemas, and metadata repositories. Maintaining operational data warehouse builds and resolving issues promptly. Ensuring adherence to agreed standards and controls for data marts and operational data stores. Leading More ❯

to ensure the opportunities and impacts of new features are fully exploited and understood, and contribute to the creation, maintenance, promotion and use of metadata resources such as Data Dictionaries and Data Lineages. Proactively engage with the business regarding projects and ensure that Data principles are being adhered to, and More ❯

to ensure the opportunities and impacts of new features are fully exploited and understood, and contribute to the creation, maintenance, promotion and use of metadata resources such as Data Dictionaries and Data Lineages. Proactively engage with the business regarding projects and ensure that Data principles are being adhered to, and More ❯

efficient data storage. • Analyze system requirements and develop strategies for migrating and integrating existing data. • Lead the design, implementation, and maintenance of databases and metadata structures, ensuring integration with corporate standards. • Stay informed of industry trends in database technology, providing strategic recommendations to improve performance and scalability. • Conduct database performance More ❯

of these investments to ensure they deliver expected outcomes and benefits. Deliver a cohesive Group Data Model to ensure consistent master data, reference data, metadata, and optimized data pipelines across processes and systems. Collaborate with market analysts, vendors, and partners to identify technological opportunities, and provide thought leadership on Data More ❯

of these investments to ensure they deliver expected outcomes and benefits. Deliver a cohesive Group Data Model to ensure consistent master data, reference data, metadata, and optimized data pipelines across processes and systems. Collaborate with market analysts, vendors, and partners to identify technological opportunities, and provide thought leadership on Data More ❯