26 to 50 of 386 Permanent Metadata Jobs

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 ❯

Strong knowledge of Python, Scala, C#, .NET. Experience with advanced SQL, T-SQL, relational databases. Azure DevOps, Terraform, BICEP, ARM templates. Distributed computing, cloud-native design patterns. Data modelling, metadata management, data quality, data as a product. Strong communication, empathy, determination, openness to innovation. Strong Microsoft Office 365 experience Interested? Please submit your updated CV to Lewis Rushton at Crimson More ❯

sources, such as SAP (via Simplement), Salesforce, OKTA, MuleSoft and JAMS Implement CI/CD deployment using Github Familiar with CloudWatch, CloudTrail, Secrets Manager for monitoring and security Manage metadata and lineage via AWS Glue Data Catalog Required Education & Experience: Bachelor's degree in related field with 8+ years of experience as a data engineer Additional years of experience may More ❯

engineering field. You'll Work With Azure Data Services: Data Factory, Data Lake, SQL Databricks: Spark, Delta Lake Power BI: Advanced dashboards and analytics ETL & Data Modelling: T-SQL, metadata-driven pipelines Design and implement scalable Azure-based data solutions Build and optimise data pipelines for integration and transformation Develop Power BI dashboards for global stakeholders Ensure data quality, governance More ❯

engineering field. You'll Work With Azure Data Services: Data Factory, Data Lake, SQL Databricks: Spark, Delta Lake Power BI: Advanced dashboards and analytics ETL & Data Modelling: T-SQL, metadata-driven pipelines Design and implement scalable Azure-based data solutions Build and optimise data pipelines for integration and transformation Develop Power BI dashboards for global stakeholders Ensure data quality, governance More ❯

of your field. 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 What you'll do Design and implement scalable Azure-based data solutions Build and optimise data pipelines for integration and transformation Develop Power BI dashboards for global stakeholders More ❯

growth and ensuring succession planning. Knowledge: * Profound understanding of data management principles, methodologies, and best practices. * Familiarity with data analytics tools, techniques, and technologies. * Strong understanding of data architecture, metadata management, and data quality techniques * Knowledge of project management methodologies, such as Agile, Scrum, or Waterfall. * Understanding of business intelligence concepts and practices. * Awareness of regulatory requirements related to data More ❯

implement data pipelines, ingestion frameworks, and transformation logic in the target Azure Databricks platform. • Collaborate with data architects and platform engineers to define target-state models, ingestion patterns, and metadata-driven frameworks. • Migrate and refactor SAS ETL logic into PySpark/SQL on Databricks following best practices. • Contribute to data quality, reconciliation, and test automation for migrated datasets. What you More ❯

implement data pipelines, ingestion frameworks, and transformation logic in the target Azure Databricks platform. • Collaborate with data architects and platform engineers to define target-state models, ingestion patterns, and metadata-driven frameworks. • Migrate and refactor SAS ETL logic into PySpark/SQL on Databricks following best practices. • Contribute to data quality, reconciliation, and test automation for migrated datasets. What you More ❯

dashboards for job failures, data quality triggers, and warehouse usage Optimize pipeline performance, concurrency, and cost governance in Snowflake Own deployment frameworks for ETL/ELT code, SQL scripts, metadata updates Support user access provisioning & RBAC alignment across Snowflake, Informatica, and Airflow Troubleshoot platform and orchestration issues, lead incident response during outages Enforce DevSecOps practices including encryption, secrets management, and More ❯

/ML initiatives (RAG workflows, LLMs, embeddings) Make Power BI dashboards that actually refresh when they're supposed to Implement governance that doesn't make people want to scream (metadata tagging, lineage tracking, the good stuff) Collaborate with brilliant behavioural scientists and product teams who'll challenge them in the best ways The ideal candidate will: Know their way around More ❯

TSC level in accordance with USAEUR-AF policies and guidance Validate Data * Implement checks to ensure data accuracy, completeness, and consistency. * Identify and resolve data anomalies or errors. Manage Metadata * Document data lineage, definitions, and transformations to ensure transparency and traceability. * Implement and manage Compliance and Security measures * Ensure data systems comply with regulations like GDPR, HIPAA, or CCPA. * Implement More ❯

data quality, including profiling, cleansing, monitoring, and remediation strategies. Provide architectural guidance on MDM platform selection, cloud vs. on-prem deployment, and integration patterns (API, ETL, messaging). Support metadata management, lineage tracking, and compliance initiatives. Skills & Experience Required: Hands-on experience with more than one MDM technology/platform (e.g., Riversand, Informatica MDM, Semarchy, TIBCO EBX, Reltio). Excellent More ❯

skills and understanding of modern data architecture principles. Hands-on experience with Tableau for enterprise-grade dashboard development. Familiarity with orchestration tools (e.g., Prefect, Airflow), data quality frameworks, and metadata tools. Proficiency in Git, CI/CD, and scripting with Python. Excellent communication skills and ability to work collaboratively across technical and business teams. More ❯

skills and understanding of modern data architecture principles. Hands-on experience with Tableau for enterprise-grade dashboard development. Familiarity with orchestration tools (e.g., Prefect, Airflow), data quality frameworks, and metadata tools. Proficiency in Git, CI/CD, and scripting with Python. Excellent communication skills and ability to work collaboratively across technical and business teams. More ❯

with analysts and business teams to align data models with reporting, AI, and automation needs. You'll also contribute to the adoption of CI/CD, version control, and metadata-driven practices that enhance scalability and trust in analytics outputs. This is a hands-on role where technical precision and design thinking come together to enable a data-first culture. More ❯

data quality , including profiling, cleansing, monitoring, and remediation strategies. Provide architectural guidance on MDM platform selection , cloud vs. on-prem deployment , and integration patterns (API, ETL, messaging). Support metadata management , lineage tracking , and compliance initiatives. Excellent communication and stakeholder management skills. Experience in multi-domain MDM (Customer, Supplier, Location, etc.) is a strong plus. Knowledge of cloud platforms (Azure More ❯

engineers, and solution architects in advanced modeling, GenAI pipelines, and prompt optimization. Evaluate and integrateenterprise and open-source AI platformsto accelerate innovation. Define data modernization roadmap - encompassing data fabric, metadata management, and data quality frameworks. Partner with enterprise architecture to ensuredata accessibility, interoperability, and AI-readiness. Lead initiatives arounddata democratizationandAI-native platform enablement(including RAG, vector databases, and feature stores More ❯

workflows to create adaptive and autonomous AI-driven solutions. Use shell scripting and scheduling tools like Zeke and Airflow to manage job execution and monitoring. Develop data dictionaries and metadata repositories to document data lineage and improve accessibility. Work closely with cross-functional teams, including business analysts, data scientists, and IT teams, to ensure seamless integration of data solutions. Create More ❯

standards. Evaluate and advise on data collection, analysis and integration technologies. Aid efforts to improve business performance through enterprise information solutions and capabilities, such as master data management (MDM), metadata management, analytics, content management, and data integration. This is a full-time, permanent role based in our Glasgow office with hybrid working. More information can be found in the job More ❯

standards. Evaluate and advise on data collection, analysis and integration technologies. Aid efforts to improve business performance through enterprise information solutions and capabilities, such as master data management (MDM), metadata management, analytics, content management, and data integration. This is a full-time, permanent role based in our Glasgow office with hybrid working. More information can be found in the job More ❯

standards. Evaluate and advise on data collection, analysis and integration technologies. Aid efforts to improve business performance through enterprise information solutions and capabilities, such as master data management (MDM), metadata management, analytics, content management, and data integration. This is a full-time, permanent role based in our Glasgow office with hybrid working. More information can be found in the job More ❯

you solve challenging problems together. Minimum Requirements Experience across UK Healthcare sector or Public Sector Strong technical design expertise in core data architecture disciplines including data modelling, data analysis, metadata management, data transformation, data migration and master data. Track record of providing technical leadership within data projects including assurance, mentoring and standards definition. Aware of best practice techniques and methodologies. More ❯

Kubernetes, Rancher, etc.). Experience with ML methods (e.g., decision trees, neural networks, reinforcement learning, etc.). An understanding and working knowledge to analyze and gain visibility to network metadata, and content, identify malicious code, anomaly detection, and potentially predictive analysis. Working knowledge in programming languages, (e.g., Python, Rust, Go, Java, etc.). Working knowledge with cloud computing platforms, (e.g. More ❯

architectures, and integration patterns. Develop and maintain cloud data frameworks using modern technologies such as Azure, AWS, or Google Cloud. Oversee end-to-end data lifecycle including ingestion, transformation, metadata management, security, and data quality. Collaborate with engineering teams, architects, and business stakeholders to define requirements and deliver data-driven solutions. Guide modernization efforts migrating legacy systems to cloud-native … databases including SQL Server, PostgreSQL, MongoDB, or Cassandra. Strong proficiency in data lake, data warehouse, and ETL/ELT design patterns. Experience with data modeling, canonical data structures, and metadata frameworks. Strong programming and scripting skills in Python, Scala, or Java. Experience with DevOps tools, CI/CD pipelines, Terraform, CloudFormation, or Kubernetes. Deep understanding of data security, compliance, and More ❯