1 to 25 of 132 Metadata Jobs in the South East

open architecture and delivery speed. Support the implementation of data governance frameworks, partnering with internal stakeholders to design and implement tools for data lineage tracking, data quality monitoring, and metadata cataloguing. Drive adoption of common standards for data access, tagging, and classification in alignment with regulatory compliance, risk, sovereignty and privacy obligations. Ensure solutions adhere to internal governance standards, including More ❯

promote the value of data across business and technology teams. Mentor data engineers, BI developers, and other stakeholders in data architecture and best practices. Maintain comprehensive architecture documentation for metadata, data lineage, and data governance. Essential Skills & Qualifications Extensive experience architecting enterprise data solutions and designing scalable data platforms. Proven expertise in data modeling (conceptual, logical, physical), metadata management, and More ❯

promote the value of data across business and technology teams Mentor data engineers, BI developers, and other stakeholders in data architecture and best practices Maintain comprehensive architecture documentation for metadata, data lineage, and data governance Essential Skills & Qualifications Extensive experience architecting enterprise data solutions and designing scalable data platforms Proven expertise in data modeling (conceptual, logical, physical), metadata management, and More ❯

and data governance Implement data quality monitoring and alerting processes. Work with data governance teams to ensure compliance with data governance policies and standards. Implement data lineage tracking and metadata management processes. Collaboration & Communication: Collaborate closely with data scientists, economists, and other technical teams to understand data requirements and translate them into technical solutions. Communicate technical concepts effectively to both More ❯

Proven expertise in designing, developing, and maintaining scalable data pipelines, ETL/ELT processes, and integrations to support advanced analytics. Experience with data governance frameworks, master data management (MDM), metadata management, and ensuring data compliance with global standards. Deep understanding of SQL, Python, Spark, or other relevant data processing technologies used for data transformation and analytics enablement. Familiarity with modern … initiatives, including the DDF program. Data Platform Optimization: Work closely with AOE data teams and PNE analytics teams to optimize the data infrastructure, ensuring performance, scalability, and cost efficiency. Metadata & Asset Management: Drive consistent metadata management and data asset governance, ensuring data reliability, accessibility, and standardization across PNE. Enablement & Best Practices: Educate and support the PNE teams in data stewardship More ❯

problems. Key responsibilities: Data Platform Design and Architecture Design, develop, and maintain a high-performing, secure, and scalable data platform, leveraging Databricks Corporate Lakehouse and Medallion Architectures. Utilise our metadata-driven data platform framework combined with advanced cluster management techniques to create and optimise scalable, robust, and efficient data solutions. Implement comprehensive logging, monitoring and alerting tools to manage the … Spark. Proven experience working with Azure data platform services, including Storage, ADLS Gen2, Azure Functions, Kubernetes. Background in cloud platforms and data architectures, such as Corporate DataLake, Medallion Architecture, Metadata Driven Platform, Event-driven architecture. Proven experience of ETL/ELT, including Lakehouse, Pipeline Design, Batch/Stream processing. Strong working knowledge of programming languages, including Python, SQL, PowerShell, PySpark … Spark SQL. Good working knowledge of data warehouse and data mart architectures. Good experience in Data Governance, including Unity Catalog, Metadata Management, Data Lineage, Quality Checks, Master Data Management. Experience using Azure DevOps to manage tasks and CI/CD deployments within an Agile framework, including utilising Azure Pipelines (YAML), Terraform, and implementing effective release and branching strategies. Knowledge of More ❯

. Hands-on experience with 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). Desirable: Background in fintech or More ❯

of SSO and MFA solutions 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, networking, security and cloud technologies More ❯

principles of data modelling Re-engineer data pipelines to be scalable, robust, automatable, and repeatable Navigate, explore and query large scale datasets Build processes supporting data transformation, data structures, metadata, dependency and workload management Identify and resolve data issues including data quality, data mapping, database and application issues Implement data flows to connect operational systems, data for analytics and business More ❯

Factory, SSIS, and Azure Data 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 plus. This role offers an More ❯

years, and is expected to grow further over the next 2-3 years. Accountabilities and Responsibilities Solid knowledge and expertise in the use of data governance, data quality, metadata, profiling, analysis, and data management tools. Drives the data definition, governance and lineage aspects 'end to end' for each Use Case assigned Responsible for monitoring changes to business data requirements and … the Financing of Terrorism (AML/CFT) space. Knowledge of the Sanctions, Transaction Monitoring, and Fraud framework, requirements and processes. Working knowledge and understanding of data governance, data quality, metadata, profiling, analysis, and data management tools. Analytically minded with experience in problem solving and being able to communicate workable solutions Understanding of data governance practices. Ability to think in an More ❯

of data warehousing, data lakes, and enterprise data architecture. Proficiency in SQL and experience working with cloud data platforms (e.g., Azure, AWS, GCP). Familiarity with data governance frameworks, metadata management, and data cataloging tools. Excellent communication and documentation skills, with the ability to explain complex data concepts to non-technical stakeholders. Preferred Skills: Experience with insurance platforms such as More ❯

and cleansing activities to support accurate keying and linking. Partner with IT and business teams to ensure governance and stewardship policies are upheld across data platforms. Develop and maintain metadata and data lineage for all keying and linking components. Evaluate and recommend tools and technologies for probabilistic and deterministic matching (e.g., Informatica MDM, IBM InfoSphere, Talend, AWS Entity Resolution). More ❯

as-code pipelines. Platform Modernisation : Drive shift from batch ETL to event-driven streaming; partner with cloud-engineering on Snowflake, Kafka, K8s. Vendor & Tooling Strategy : Rationalise BI, MDM, and metadata tooling; negotiate enterprise licences. Leadership & Change : Build and mentor a 20-30 FTE cross-location data-architecture guild; embed OKRs and agile ways of working. Profile We’re After More ❯

Spark/Scala Data structures (tables, views, stored procedures) Data Modelling - star/snowflake Schemas, efficient storage, normalisation Data Transformation DevOps - data pipelines Controls - selection and build Reference and metadata management What else you need to know: This role is based in Unity Place - Milton Keynes. We want our people to thrive at work and home, and also be able More ❯

industry trends. Develop cost models, risk assessments, and business cases for proposed solutions. Skills Required Strong technical design expertise in core data architecture disciplines including data modelling, data analysis, metadata management, data transformation, data migration and master data. Experience in establishing data analytics and supporting AI solutions. Good working knowledge of ontologies and taxonomies. Data quality/validation experience: designing More ❯

EDC, and Axon. Troubleshooting and technical support for IDQ, EDC, and Axon platforms. Manage data profiling, scorecard creation, reference tables, and data quality metrics. Implement Data Catalog, Data Lineage, Metadata Management, and Data Governance standards. Integration with enterprise systems including SSO, ServiceNow, and other third-party platforms. Performance tuning, capacity planning, and environment optimization. Collaborate with infrastructure teams for system … line utilities. Solid experience with AWS services (EC2, RDS, S3, Route 53, etc.). Expertise with Oracle and MS SQL Server databases. Demonstrated experience in enterprise data governance and metadata management. Ability to analyze and resolve complex technical issues. Strong stakeholder management and communication skills. Desirable: Informatica IDQ Developer/Admin certification. Experience with ETL, Active Directory integration, Chef, and More ❯

Talend, dbt). Experience designing 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 of data security and compliance More ❯

Talend, dbt). Experience designing 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 of data security and compliance More ❯

Talend, dbt). Experience designing 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 of data security and compliance More ❯

Talend, dbt). Experience designing 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 of data security and compliance More ❯

Talend, dbt). Experience designing 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 of data security and compliance More ❯

Talend, dbt). Experience designing 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 of data security and compliance More ❯

and delivering modern data platforms at scale Familiar with TOGAF and other enterprise architecture frameworks Experience and knowledge of data governance, data quality, and data cataloguing Knowledge of master, metadata and reference data management An understanding of Agile working practices and sprint based methodology Capable of actively contributing to knowledge sharing Desirable Knowledge, Skills and Experience: Knowledge of genomics Experience More ❯

user needs when designing deliverables. 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 of service-oriented architecture, including More ❯