1 to 25 of 103 Metadata Jobs in the Midlands

with governance policies and regulatory standards Collaborate with enterprise architects, DBAs and infrastructure teams to optimize data performance security Develop and maintain data lineage, metadata and architecture documentation Support reporting and analytics initiatives by ensuring data availability and consistency across systems Assist in designing data integration using tools such as More ❯

with governance policies and regulatory standards Collaborate with enterprise architects, DBAs and infrastructure teams to optimize data performance security Develop and maintain data lineage, metadata and architecture documentation Support reporting and analytics initiatives by ensuring data availability and consistency across systems Assist in designing data integration using tools such as 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 ❯

/Responsibilities: Design and implement logical and physical database structures for enterprise applications and data warehouses. Develop and maintain data models, ER diagrams, and metadata repositories. Create, tune, and monitor database objects such as tables, views, indexes, stored procedures, and triggers. Optimize SQL queries and database configurations to ensure high More ❯

related to the project implementation Your Skills and Experience Experience with Ab Initio: • Extensive experience working with Ab Initio Co>OP, GDE, express>It, Metadata hub, Authorisation Gateway software. • Good understanding of Ab Initio concepts like checkpoints, parallelism, graph dynamic layouts • Continuous Flows in Ab Initio • Good knowledge of the More ❯

and tools. You will contribute in pre-sales and design, implement scalable data architectures, and information solutions covering data security, data privacy, data governance, metadata management, multi-tenancy and mixed workload management, and provide delivery oversight. Here's how you'll contribute: Senior Data Architect at Zensar participates in end More ❯

ensure performance, reliability, and data quality Collaborate with business stakeholders, and analysts to deliver clean, curated datasets and data products Contribute to data governance, metadata management, and data cataloguing initiatives Cooper Parry is a company that is always focused on optimisation and looking at new ways to improve how we More ❯

command of data transformation and pipeline tools, such as DBT, Apache Spark, or equivalent. Expertise in implementing data governance frameworks, including data quality management, metadata management, and data security practices. Experience leading cross-functional data governance initiatives and councils. Ability to translate complex business requirements into scalable technical solutions. Proficient More ❯

business goals. Lead the implementation of a Data Catalogue and Governance Suite (e.g., Collibra, Alation, Informatica). Design and maintain data models, lineage, and metadata standards. Collaborate with business and enterprise stakeholders to establish data ownership and governance. Enable a Data-Driven Operating Model (DDOM) – embedding data literacy and strategy More ❯

modelling tools and techniques Expertise in database design and understanding of relational and non-relational database systems Knowledge of data governance , data quality, and metadata management practices Familiarity with Microsoft Azure and Databricks environments Ability to clearly translate business needs into technical data models Analytical mindset with a logical approach More ❯

and implementing scalable data pipelines and integration patterns across structured and unstructured data sources (e.g., Azure SQL, MySQL, MongoDB). Familiarity with data governance, metadata management, and data quality frameworks. Practical experience applying DevOps principles to data engineering, including CI/CD pipelines, infrastructure as code, and monitoring. Solid understanding More ❯

and implementing scalable data pipelines and integration patterns across structured and unstructured data sources (e.g., Azure SQL, MySQL, MongoDB). Familiarity with data governance, metadata management, and data quality frameworks. Practical experience applying DevOps principles to data engineering, including CI/CD pipelines, infrastructure as code, and monitoring. Solid understanding More ❯

and implementing scalable data pipelines and integration patterns across structured and unstructured data sources (e.g., Azure SQL, MySQL, MongoDB). Familiarity with data governance, metadata management, and data quality frameworks. Practical experience applying DevOps principles to data engineering, including CI/CD pipelines, infrastructure as code, and monitoring. Solid understanding More ❯

and implementing scalable data pipelines and integration patterns across structured and unstructured data sources (e.g., Azure SQL, MySQL, MongoDB). Familiarity with data governance, metadata management, and data quality frameworks. Practical experience applying DevOps principles to data engineering, including CI/CD pipelines, infrastructure as code, and monitoring. Solid understanding More ❯

and implementing scalable data pipelines and integration patterns across structured and unstructured data sources (e.g., Azure SQL, MySQL, MongoDB). Familiarity with data governance, metadata management, and data quality frameworks. Practical experience applying DevOps principles to data engineering, including CI/CD pipelines, infrastructure as code, and monitoring. Solid understanding More ❯

and implementing scalable data pipelines and integration patterns across structured and unstructured data sources (e.g., Azure SQL, MySQL, MongoDB). Familiarity with data governance, metadata management, and data quality frameworks. Practical experience applying DevOps principles to data engineering, including CI/CD pipelines, infrastructure as code, and monitoring. Solid understanding More ❯

and implementing scalable data pipelines and integration patterns across structured and unstructured data sources (e.g., Azure SQL, MySQL, MongoDB). Familiarity with data governance, metadata management, and data quality frameworks. Practical experience applying DevOps principles to data engineering, including CI/CD pipelines, infrastructure as code, and monitoring. Solid understanding More ❯

and implementing scalable data pipelines and integration patterns across structured and unstructured data sources (e.g., Azure SQL, MySQL, MongoDB). Familiarity with data governance, metadata management, and data quality frameworks. Practical experience applying DevOps principles to data engineering, including CI/CD pipelines, infrastructure as code, and monitoring. Solid understanding More ❯

and implementing scalable data pipelines and integration patterns across structured and unstructured data sources (e.g., Azure SQL, MySQL, MongoDB). Familiarity with data governance, metadata management, and data quality frameworks. Practical experience applying DevOps principles to data engineering, including CI/CD pipelines, infrastructure as code, and monitoring. Solid understanding More ❯

and implementing scalable data pipelines and integration patterns across structured and unstructured data sources (e.g., Azure SQL, MySQL, MongoDB). Familiarity with data governance, metadata management, and data quality frameworks. Practical experience applying DevOps principles to data engineering, including CI/CD pipelines, infrastructure as code, and monitoring. Solid understanding More ❯

and implementing scalable data pipelines and integration patterns across structured and unstructured data sources (e.g., Azure SQL, MySQL, MongoDB). Familiarity with data governance, metadata management, and data quality frameworks. Practical experience applying DevOps principles to data engineering, including CI/CD pipelines, infrastructure as code, and monitoring. Solid understanding More ❯

and implementing scalable data pipelines and integration patterns across structured and unstructured data sources (e.g., Azure SQL, MySQL, MongoDB). Familiarity with data governance, metadata management, and data quality frameworks. Practical experience applying DevOps principles to data engineering, including CI/CD pipelines, infrastructure as code, and monitoring. Solid understanding More ❯

Experience in designing technology solutions with complex end-to-end data flows. Experience in implementing data governance, including data cataloging, data lineage tracking, and metadata management to ensure data accuracy, accessibility, and compliance. Preferred: Experience with Databricks Understanding of how data platforms interact with marketing and customer engagement platforms. Knowledge More ❯

Experience in designing technology solutions with complex end-to-end data flows. Experience in implementing data governance, including data cataloging, data lineage tracking, and metadata management to ensure data accuracy, accessibility, and compliance. Preferred: Experience with Databricks Understanding of how data platforms interact with marketing and customer engagement platforms. Knowledge More ❯

Experience in designing technology solutions with complex end-to-end data flows. Experience in implementing data governance, including data cataloging, data lineage tracking, and metadata management to ensure data accuracy, accessibility, and compliance. Preferred: Experience with Databricks Understanding of how data platforms interact with marketing and customer engagement platforms. Knowledge More ❯