1 to 25 of 384 Permanent Metadata Jobs

products and support others to do the same Other Skills Proficiency in developing and maintaining complex data models (conceptual, logical and physical). Strong skills in data governance and metadata management. Experience with data integration design and implementation. Ability to write efficient, maintainable code for large scale data systems. Experience with CI/CD pipelines, version control, and infrastructure-as More ❯

and platforms. BI Development & Engineering Oversee development of dashboards, visualizations, reporting solutions, and data models. Build and optimize ETL/ELT pipelines supporting the BI ecosystem. Implement data governance, metadata management, and data quality frameworks. Ensure BI solutions meet performance, availability, and security requirements. Stakeholder Collaboration Partner with business teams to translate requirements into BI solutions. Work with data engineering More ❯

Architect and optimize ETL/ELT pipelines for batch and streaming workloads. Develop data ingestion frameworks using APIs, messaging platforms, and cloud-native services. Ensure data quality, governance, and metadata standards are integrated into all data solutions. Leadership & Collaboration Provide technical leadership to data engineers, developers, and cross-functional teams. Partner with business and IT stakeholders to translate requirements into More ❯

Lead the design and implementation of data models, pipelines, and integration frameworks. Support the implementation of Customer Data Platforms (CDPs), MDM, and CRM systems. Ensure compliance with data governance, metadata standards, and data quality frameworks. Collaborate with stakeholders to define data architecture vision and roadmap. Contribute to the development of reusable architecture assets and design patterns. Mentor junior team members More ❯

Lakehouse design and modeling (Kimball, OLAP, OLTP, Star/Snowflake schemas Proficiency in CI/CD, Git, Docker, Kubernetes, Airflow or similar orchestration tools. Knowledge of data governance, security, metadata management, and data quality frameworks. Nice to Have Experience with Databricks/Snowflake/Delta Lake. Exposure to ML pipelines, MLOps, and real-time streaming data processing. Experience in designing More ❯

data modelling, governance, and architecture best practices . Excellent leadership, communication, and stakeholder management skills. NICE TO HAVE: Background in data management, engineering, or database administration . Experience with metadata management and master data management (MDM) tools. Understanding of data governance frameworks and compliance standards. Familiarity with machine learning pipelines or AI model integration. A proactive, detail-oriented approach and More ❯

understand data requirements and develop appropriate data solutions. Identify, create, prepare data required for advanced analytics, visualization, reporting, and AI/ML. Implement data migration, data integrity, data quality, metadata management, and data security functions to optimize data pipelines. Monitor and troubleshoot data related issues to maintain high availability and performance. Actively support Agile DevOps process, including Program Increment planning. More ❯

reliable datasets. Implement data quality monitoring, validation processes, and performance optimisation. Support AI initiatives by designing AI marts, feature engineering structures, and ML-ready datasets. Contribute to standardised KPIs, metadata, and a single source of truth for reporting. Work with business teams to translate complex requirements into scalable, high-impact models. Support agile delivery of data products and continuous improvement More ❯

Azure Data Factory, Synapse Analytics, Data Lake Storage, Stream Analytics, Event Hubs. Proficient in Python, Scala, C#, .NET, and SQL (T-SQL). Skilled in data modelling, quality, and metadata management. Experience with CI/CD and Infrastructure as Code using Azure DevOps and Terraform. Strong analytical, communication, and stakeholder engagement skills. Exposure to machine learning engineering is desirable. Interested More ❯

features: schema design, micro-partitioning, warehouses, tasks, streams, and Snowpark. Familiarity with replication and transformation tools (Airbyte, DBT) and cloud ecosystems (AWS preferred). Strong understanding of data governance, metadata, and lineage frameworks. Experience enabling BI tools (e.g., Power BI) through Snowflake data models. Desirable: Experience in data migration, change management, and enterprise rollout of modern data platforms. What you More ❯

PowerApps, Power Automate, Power BI, Python, and SharePoint. Solid understanding of data engineering, ETL processes, DataIKU, and data integration. Experience in data governance or data-management roles (data quality, metadata, controls). Demonstrated project-management ability across complex technical initiatives. Excellent analytical, problem-solving, communication, and stakeholder-management skills. Please send your CV for consideration. More ❯

workflows for performance and scalability. Responsibilities Design, build, and manage scalable data pipelines to ingest and process large datasets from diverse sources. Develop and maintain data models, schemas, and metadata documentation. Implement data integration solutions using ETL/ELT processes. Monitor and troubleshoot data systems to ensure data accuracy and system reliability. Collaborate with cross-functional teams to understand data More ❯

clients. In this role, you'll be at the heart of transforming legacy systems into scalable, production-grade architectures using Microsoft Fabric. You'll build complex ingestion pipelines, craft metadata-driven transformation layers, optimise data workflows, and deliver high-quality semantic models that power enterprise reporting. You'll work across Microsoft Fabric, Power BI, Power Platform, Dynamics 365, and Business More ❯

clients. In this role, you'll be at the heart of transforming legacy systems into scalable, production-grade architectures using Microsoft Fabric. You'll build complex ingestion pipelines, craft metadata-driven transformation layers, optimise data workflows, and deliver high-quality semantic models that power enterprise reporting. You'll work across Microsoft Fabric, Power BI, Power Platform, Dynamics 365, and Business More ❯

and CI/CD for data pipelines. BI/Visualisation: Familiarity with BI and visualisation tools such as Tableau, QuickSight, or similar. Data Governance Tools: Experience with data cataloguing, metadata management, and data lineage tools. Contextual Understanding: Passionate about data quality, governance, and understanding the business context behind the data. This role is London-based and operates on a hybrid More ❯

and CI/CD for data pipelines. BI/Visualisation: Familiarity with BI and visualisation tools such as Tableau, QuickSight, or similar. Data Governance Tools: Experience with data cataloguing, metadata management, and data lineage tools. Contextual Understanding: Passionate about data quality, governance, and understanding the business context behind the data. This role is London-based and operates on a hybrid More ❯

engineers. Excellent problem-solving skills and experience in agile environments. Desirable: Experience with streaming data (Kafka/Kinesis), Docker/Kubernetes, Terraform, CI/CD pipelines, NoSQL databases, and metadata management tools. Company Benefits: Enhanced Parental Leave Generous annual leave Healthcare Plan Annual Giving Day - an extra day to give back to yourself or your community Cycle-to-work Scheme More ❯

definition and implementation of an enterprise data model (EDM) thatleverages the latest technologies to support system performance, scalability,security, and data analytics for Threes data. What else it involves Metadata and MDM (MasterData Management) Assist in assessing theeffectiveness of existing technologies and processes in relation to thedata architecture Create necessaryimplementation/migration plans, and recommend new solutions as requiredwith a More ❯

Wherescape, ERwin, ER/Studio) Excellent communication and documentation skills. Nice to Have: Certifications in Google Cloud Platform Professional Data Engineer or Architect. Experience with data governance frameworks and metadata management. Exposure to data product lifecycle and data mesh principles. Experience with ER. More ❯

Wherescape, ERwin, ER/Studio) Excellent communication and documentation skills. Nice to Have: Certifications in Google Cloud Platform Professional Data Engineer or Architect. Experience with data governance frameworks and metadata management. Exposure to data product lifecycle and data mesh principles. Experience with ER. More ❯

or XML APIs Familiarity with CI/CD pipelines (GitHub Actions, Azure DevOps, etc.). Exposure to Infrastructure as Code experience (Terraform, CloudFormation). Experience with data governance and metadata tools (Atlan, OpenMetadata, Collibra). Public health/healthcare dataset or similar experience, including PHI/PII handling. Familiarity with SAS and R workflows to support epidemiologists and analysts. Experience More ❯

Administer Microsoft Fabric Lakehouse and Azure services Optimise performance across queries, datasets, and pipelines Apply data validation, cleansing, and standardisation rules Document pipeline logic and contribute to business-wide metadata catalogues Collaborate with BI, Change, and Product teams to align data outputs to needs Support groundwork for future data science and machine learning initiatives The successful applicant will be proficient More ❯

best practices: Promote robust data management, including lineage, observability, access control, and compliance with ethical data use. Innovation&standards: Stay ahead of industry trends in data architecture, engineering, and metadata/semantic technologies—and bring them into practice where they add value. Enterprise data architecture: Collaborate with other architects to define and implement data architecture patterns across systems and domains More ❯

best practices: Promote robust data management, including lineage, observability, access control, and compliance with ethical data use. Innovation&standards: Stay ahead of industry trends in data architecture, engineering, and metadata/semantic technologies—and bring them into practice where they add value. Enterprise data architecture: Collaborate with other architects to define and implement data architecture patterns across systems and domains More ❯

make an impact. What You'll Work With Azure Data Services: Data Factory, Data Lake, SQL Databricks: Spark, Delta Lake Power BI: Advanced dashboards ETL & Data Modelling: T-SQL, metadata-driven pipelines DevOps: CI/CD Bonus: Python What you'll do Design and implement scalable Azure-based data solutions Build and optimize data pipelines for integration and transformation Develop More ❯