26 to 50 of 251 DemandTrendPermanent Metadata Jobs

design, dbt, Airflow. Experience with Infrastructure as Code (Terraform), CI/CD (GitHub), and monitoring (e.g., Datadog, Grafana, Prometheus). Understanding of data governance, Unity Catalog, cost monitoring, and metadata management are an advantage. Initial experience with Jira and Confluence is desirable. Strong communication skills, team orientation, and an agile way of working. You are a team player with a More ❯

design, dbt, Airflow. Experience with Infrastructure as Code (Terraform), CI/CD (GitHub), and monitoring (e.g., Datadog, Grafana, Prometheus). Understanding of data governance, Unity Catalog, cost monitoring, and metadata management are an advantage. Initial experience with Jira and Confluence is desirable. Strong communication skills, team orientation, and an agile way of working. You are a team player with a More ❯

design, dbt, Airflow. Experience with Infrastructure as Code (Terraform), CI/CD (GitHub), and monitoring (e.g., Datadog, Grafana, Prometheus). Understanding of data governance, Unity Catalog, cost monitoring, and metadata management are an advantage. Initial experience with Jira and Confluence is desirable. Strong communication skills, team orientation, and an agile way of working. You are a team player with a More ❯

emerging technologies, and market trends, advising leadership on best practices. • Communicate effectively with end-users, support staff, management, and other departments on all data-related initiatives. • Establish and maintain metadata management, data lineage, and cataloging to enhance discoverability and usability across the organization. • Assist other teams with the integration, implementation, and troubleshooting of projects involving local, cloud, and hybrid network More ❯

/or Scala. * Expertise in ETL/ELT processes, 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 cataloguing. * Knowledge of serverless data processing, event-driven architectures, and modern data stacks. In accordance with the Employment Agencies and Employment Businesses Regulations More ❯

Analytical Data Engineer Job Requirements Essential 2-5 years' experience in data modelling. Advanced level in application-based data modelling and ETL. Strong background in data analysis, cleansing, enrichment, metadata management, and data innovation. Proficiency in SQL and MySQL. Experience with business intelligence tools: Power BI, Sisense, Quicksight. Hands-on experience with ETL tools, Sagemaker or Unified Studio (one of More ❯

Analytical Data Engineer Job Requirements Essential 2-5 years' experience in data modelling. Advanced level in application-based data modelling and ETL. Strong background in data analysis, cleansing, enrichment, metadata management, and data innovation. Proficiency in SQL and MySQL. Experience with business intelligence tools: Power BI, Sisense, Quicksight. Hands-on experience with ETL tools, Sagemaker or Unified Studio (one of More ❯

medallion-based architecture, with curated dimensional models in the gold layer built for analytical use Strong understanding and or use of unity catalog alongside core databricks functionality to drive metadata management Strong understanding of cloud economics, including cost management strategies and optimising solutions for customer needs. Experience with infrastructure as code, proficiency using tools such as Terraform to automate and More ❯

transactional, analytical, and operational systems Architect solutions for data lakes, warehouses, and master data management (MDM) Establish reference architecture for data ingestion, transformation, storage, and consumption Champion data quality, metadata, and governance standards (including GDPR compliance) Provide architectural oversight on multi-cloud and hybrid environments Collaborate with stakeholders to enable data-driven decision-making and new revenue streams Skills & Experience More ❯

and OneLake architecture, ensuring scalability, performance, and security. Oversee data ingestion, transformation, and modelling, integrating both internal and external datasets. Maintain and enforce data governance frameworks, including KPI definitions, metadata management, and GDPR/compliance adherence. Embed ethical AI and responsible data practices, ensuring transparency, fairness, and explainability in AI models. Reporting, Visualisation & Advanced Analytics Lead the design and delivery More ❯

physical data models to support business and technical requirements. Collaborate with data architects, analysts, and engineers to ensure accurate translation of business needs into data solutions. Maintain data dictionaries, metadata, and documentation for consistency and reusability across the organization. Optimize data models for performance, scalability, and integration with existing systems. Ensure compliance with data governance, security, and quality standards. Support More ❯

physical data models to support business and technical requirements. Collaborate with data architects, analysts, and engineers to ensure accurate translation of business needs into data solutions. Maintain data dictionaries, metadata, and documentation for consistency and reusability across the organization. Optimize data models for performance, scalability, and integration with existing systems. Ensure compliance with data governance, security, and quality standards. Support 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 ❯

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 ❯

understanding of the trade and portfolio management lifecycle, operations, compliance, risk, and attribution reporting. Demonstrated experience in data management, including DQ value, processes, tools, and related activities (data governance, metadata, data standards, data aggregation). A collaborative, team-oriented mindset with a passion for continuous learning and innovation. Experience presenting to and influencing executive-level stakeholders and contributing to enterprise More ❯

consistent data standards across the enterprise. Provide technical support and customer service to both headquarters and field users. Oversee the PSP system's content, auditing for missing or inappropriate metadata, and escalate technical issues as necessary. Ensure the efficient scheduling, processing, and documentation of data delivery and implementation, leveraging automation when feasible. Required Qualifications: Active Top Secret security clearance Bachelor More ❯

not limited to, the following capabilities: Essential Job Functions: Architect, design, code, and implement next-generation data analytics using best practices in the latest technologies. Develop solutions to enable metadata/rules engine-driven data analytics application leveraging open source and/or cloud native components. Develop solutions in a highly collaborative and agile environment. Lead efforts in collecting, normalizing More ❯

star and snowflake 5+years' experience with data modeling tools like Erwin, ER/Studio or Archi 3+years' experience with data management activities data quality, master data management, data governance, metadata management 2+years' experience in establishing data dictionaries, data models and documenting technical requirements 2+ years of development or DBA experience in RDBMS systems 5+ years strong SQL experience 2+years' experience More ❯

and SQL across platforms like Snowflake, real-time systems, or similar Strong exposure to AWS (Lambda, S3, EKS, SNS, API Gateway) Understanding of real-time and analytical data pipelines, metadata, and cataloguing (e.g., Atlan) Strong communication, stakeholder management, and documentation skills Preferred (but not essential): AWS or Snowflake certifications Knowledge of Apache Airflow, DBT, GitHub Actions Experience with Iceberg tables More ❯

physical systems, ensuring secure and 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 evaluations, risk assessments, and financial More ❯

and budgeting processes with evidence based models. Ensure all data handling complies with GDPR, SRA regulations and internal policies. Support data governance initiatives, including data quality and audits and metadata management. Profile Proven experience as a data analyst or business intelligence analyst ideally within a professional services environment. Proficient in Power BI, Excel (pivot tables, Power Query, etc.), and SQL. More ❯

technical leadership skills. PREFERRED SKILLS: • Experience in DoD environments or IL5/IL6 cloud instances. • Knowledge of ITIL, data governance, and federated data standards. • Background in architecture frameworks and metadata management. COMPENSATION: • Excellent compensation commensurate with experience in related field(s) and performance • Major medical, dental, and vision • Paid holidays • Paid Time Off (PTO) Job Type: Full-time Compensation Package More ❯

into a unified data platform. Cleanse, transform, and model data to support BI tools (e.g., Power BI) and AI/ML use cases. Implement data validation, lineage tracking, and metadata tagging for observability and trust. Collaborate with stakeholders to standardise KPIs and support cross-functional reporting. Ensure secure handling of sensitive data in line with GDPR and internal policies. What More ❯

into a unified data platform. Cleanse, transform, and model data to support BI tools (e.g., Power BI) and AI/ML use cases. Implement data validation, lineage tracking, and metadata tagging for observability and trust. Collaborate with stakeholders to standardise KPIs and support cross-functional reporting. Ensure secure handling of sensitive data in line with GDPR and internal policies. What More ❯

into a unified data platform. Cleanse, transform, and model data to support BI tools (e.g., Power BI) and AI/ML use cases. Implement data validation, lineage tracking, and metadata tagging for observability and trust. Collaborate with stakeholders to standardise KPIs and support cross-functional reporting. Ensure secure handling of sensitive data in line with GDPR and internal policies. What More ❯