76 to 100 of 749 Metadata Jobs

reporting workloads. Experience with cloud-native data technologies or modern data platform tooling. Experience with Data Orchestration/ETL processes. Understanding of data governance, metadata management, data quality and data lineage practices. Awareness of AI-assisted tooling and its responsible use within data engineering and architecture. Qualifications Not essential ...

architectural integrity rather than hands‐on coding. Ensuring Governance & Quality: Establish Strong Data Governance, partner with the Data Governance Manager to define schema management, metadata frameworks (e.g., OpenMetadata), and data quality controls, promoting data democratisation and self-service. Adhere to Security & Compliance by integrating information security standards and FDJ United ...

analytical or historical reporting workloads.Experience with cloud-native data technologies or modern data platform tooling.Experience with Data Orchestration/ETL processes.Understanding of data governance, metadata management, data quality and data lineage practices.Awareness of AI-assisted tooling and its responsible use within data engineering and architecture.QualificationsNot essential to be successful ...

platform architectures. Deep knowledge of ETL/ELT, APIs, integration patterns, data pipelines, and event-based integration. Understanding of master data management, data governance, metadata, lineage, and data quality. Understanding of security, privacy, compliance, and data integrity requirements. Ability to evaluate complex business requirements and develop pragmatic, scalable technical solutions. ...

data architecture transformation Experience with business capability models, process taxonomies and maturity assessments Experience designing or governing data platform architectures , including data quality, metadata, security, privacy and compliance Understanding of public and private cloud architectures Experience with hyperscale and enterprise platforms (e.g. SAP, Workday, Oracle, Salesforce, public cloud providers) Experience ...

Automation Define architecture patterns, governance standards, security controls, and best practices for enterprise AI adoption. Apply GenAI capabilities to areas such as data transformation, metadata management, customer service, risk, compliance, operations, and process automation. Collaborate with engineering, data, cloud, and business teams to ensure successful delivery and adoption. Drive solution ...

reporting workloads. Experience with cloud-native data technologies or modern data platform tooling. Experience with Data Orchestration/ETL processes. Understanding of data governance, metadata management, data quality and data lineage practices. Awareness of AI-assisted tooling and its responsible use within data engineering and architecture. Qualifications Not essential ...

skills: CTEs, window functions, LATERAL joins, performance tuning, and complex multi-source financial queries Production dbt experience: modular models, tests, documentation, and semantic metadata for both AI and BI consumers Snowflake proficiency: roles, warehouses, governance, masking policies, and row-level security - not just querying, but owning the environment Experience supporting ...

skills: CTEs, window functions, LATERAL joins, performance tuning, and complex multi-source financial queries Production dbt experience: modular models, tests, documentation, and semantic metadata for both AI and BI consumers Snowflake proficiency: roles, warehouses, governance, masking policies, and row-level security -- not just querying, but owning the environment Experience supporting ...

partner effectively with strong communication skills to translate technical trade-offs, risks and business value for senior stakeholders. Experience with clinical data standards, metadata management, validated computing environments, cloud platforms, version control or related technology platforms. Knowledge & Experience (preferred): Experience in oncology, rare disease, neuroscience or specialty-care clinical development. ...

Azure) and Data Lakehouse Architectures You have experience of designing and implementing technical data governance strategies with a focus on data quality and discoverable metadata, with practical knowledge of data-mesh or data-product-oriented architectures You are passionate about communicating complex concepts succinctly to both technical and non-technical ...

Azure) and Data Lakehouse Architectures You have experience of designing and implementing technical data governance strategies with a focus on data quality and discoverable metadata, with practical knowledge of data-mesh or data-product-oriented architectures You are passionate about communicating complex concepts succinctly to both technical and non-technical ...

cloud architects, security teams, and customer stakeholders to deliver high-quality data solutions. Governance & Security: Establish and enforce governance frameworks covering data quality, lineage, metadata management, access controls, and regulatory compliance. Documentation: Produce and maintain architecture artefacts, standards, patterns, and technical documentation. Future Technology: Guide customers on emerging technologies including … Cloud and/or Databricks Lakehouse Platform. Strong knowledge of cloud-native data architectures across Azure and AWS Strong understanding of data governance, security, metadata management, and data lifecycle management. Understanding of AI/ML data requirements and modern analytics platforms. Knowledge of big data processing frameworks and distributed computing ...

Price Verification (IPV) platform supporting a global Refined Product Trading organization. The Solution Architect will define the end-to-end architecture for a governed, metadata-driven IPV Control Hub that replaces fragmented Excel, Microsoft Access, VBA, and email-based processes with an automated, controlled, and SOX-compliant enterprise solution. … reusable components. Design scalable Dataiku processing frameworks that support more than 70 internal and external data sources, including structured and unstructured data. Define metadata-driven frameworks for managing brokers, source priorities, mappings, thresholds, currencies, units of measure, regional variations, approval paths, and business rules. Design reusable Dataiku project templates ...

/data pipelines Data modelling, lakehouse architecture and modern data platforms Azure data services API and third-party system integration Data quality, governance, metadata and lineage Git, CI/CD and engineering best practices This role would suit someone who enjoys solving complex data challenges, thinks beyond individual pipelines ...

skills and practical experience using Python for data analysis and data quality activities, together with a solid understanding of data governance, master data management, metadata, lineage, classification, data quality frameworks, data lifecycles and maturity models. You will also have a good understanding of data protection, GDPR, data security, privacy ...

Databricks and related services. Develop and maintain datasets and data models that support analytics and reporting, following established modelling standards Contribute to data lineage, metadata management and cataloguing practices, including exposure to Purview Work closely with the Lead Data Engineer, Analysts and Architects to develop and improve engineering standards ...

data platforms using AWS and/or Azure, alongside modern platforms such as Snowflake. Experience designing architectures for unstructured data, knowledge graphs, semantic models, metadata frameworks, taxonomies, ontologies, or enterprise search solutions using technologies such as RDF, OWL, SPARQL, or similar. Understanding of AI technologies, including large language models, vector ...

Ensure architecture supports UK GDPR, data minimisation, DPIAs, data-sharing requirements, information governance and wider public sector obligations Enhance Microsoft Purview integration for cataloguing, metadata, lineage, ownership, classification and discoverability; define accountability for domains, workspaces, data products and semantic models Review capacity, performance and consumption, recommending workload protection, monitoring, cost ...

frameworks, scripting). Experience supporting or validating ETL/ELT pipelines and data quality frameworks (rules, thresholds, exception handling). Exposure to lineage and metadata approaches; ability to validate transformations and trace data across platforms. Tooling/Delivery Methods Working knowledge of scheduling/orchestration tools such as Autosys ...

Have Experience with TypeScript or JavaScript Experience contributing to frontend applications (React) Familiarity with observability tooling (logging, monitoring, tracing) Experience with data modelling and metadata management Exposure to CI/CD practices for data pipelines and services Experience working in delivery-focused, agile environments Please note: We offer flexible hybrid ...

different approaches and techniques, whilst ensuring we apply industry-recognised data modelling patterns and standards. Work with team members to create, manage and maintain metadata standards, practices and tools. Design data architecture that deals with problems spanning different business areas, including maintaining & updating existing patterns or creating new, when necessary. ...

providing technical specifications and solution architecture for data flows. Technical proficiency in tools such as SQL, Python, ETL platforms, API gateways, Snowflake, Databricks, and metadata management platforms. To be successful in this role, were seeking the following: Bachelors degree or the equivalent Advanced/graduate degree preferred Severeal years ...

Python. Use data & artificial intelligence tools (e.g., AWS, CoPilot, Snowflake, DataBricks, LLM). Understanddata management and governance, including data platforms, pipelines, models, taxonomies, metadata, lineage, privacy, and regulatory compliance. Applystrong quantitative and analytical problem-solving skills to design experiments and deliver measurable outcomes (e.g., key performance indicators, uplift, return ...

transformation patterns Data integration, orchestration, APIs and event-driven architecture Logical, physical and semantic data design Data product schemas, interfaces and data contract design Metadata, data catalogue and lineage implementation patterns Data security engineering, privacy, identity and access-control patterns Performance, scalability, workload and cost optimisation DevOps/DataOps practices ...