51 to 75 of 411 Permanent Metadata Jobs

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 ❯

and equality of opportunity for all. Senior Responsibilities Taking a specific area of accountability on data ecosystem solution architecture, e.g., master data management, reference data management, enterprise data catalogue, metadata Taking a specific area of responsibility in organisation wide data policies, e.g., data privacy, data archival, data lifecycle management, data processing, data analysis Ensuring specific areas of accountability and responsibility 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 ❯

technologies and industry trends. Develop cost models, risk assessments, and business cases for proposed solutions. Skills Required Essential: Strong expertise in data architecture, including data modelling, analysis, transformation, migration, metadata, and master data management. Experienced delivering data analytics solutions and supporting AI initiatives. Hands on experience with cloud data platforms, ideally AWS (S3, Kinesis, Glue, Redshift, Lambda, EMR) and/ More ❯

architecture and design of an enterprise-scale AWS-based data lake and data integration ecosystem to support advanced analytics and AI/ML initiatives. Define and enforce data modeling, metadata, data lineage, and data governance standards to support analytics and machine learning workflows Establish best practices in data architecture, including schema design, data normalization, and optimal format selection (e.g., Parquet … of experience designing and implementing cloud-native data solutions in AWS, including services such as Glue, S3, Athena, Redshift, Lake Formation, Step Functions, and Lambda. Experience in data modeling, metadata management, and data governance frameworks. Understand ETLconcepts of data flow, data enrichment, data consolidation, change data capture and transformation Hands-on experience architecting data lakes, data warehouses, and real-time More ❯

and innovation Technology Cloud & Data Platforms: Azure Synapse, Azure Data Lake, Azure Data Factory Data Modelling & Integration: SQL, ETL tools, data pipelines Architecture & Governance: Enterprise data models, data catalogues, metadata management Collaboration & Documentation: Agile delivery, architecture documentation, stakeholder workshops Join a business where data is at the heart of decision-making and where you can work on exciting projects that 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 ❯

succeed You'll bring extensive experience in data engineering within Azure environments, with a strong track record in modernisation and large-scale migration projects. You'll be confident designing metadata-driven frameworks and managing Databricks environments, with hands-on expertise in Python, T-SQL, and PySpark. Your leadership and mentoring skills will be key, alongside your ability to collaborate across More ❯

Developer) or PL-600 (Solution Architect) strongly preferred. Proven expertise in Dataverse schema design, Power BI dashboarding, and enterprise data integration. Strong knowledge of data governance, compliance, and metadata management. Minimum of an active DoD Secret clearance required. Candidates without a minimum of a Secret clearance will not be considered. We invest in the lives of our employees, both in More ❯

to at least 3NF Strong knowledge of database structure systems and data mining Proficient in Kimball methodology and Data Vaults Deep understanding of database fundamentals and experience in designing metadata-driven ingestion and transformation pipelines. Experienced in Master Data Management (MDM), data cataloguing, and managing data lineage Familiarity with accelerators and extensive knowledge of Azure Cloud Services including DataBricks, Azure More ❯

Large-scale data architecture, data modeling, database design, and information systems implementation Demonstrated knowledge and expertise in enterprise data strategy, data governance practices, data stewardship principles, data standards, and metadata management best practices Ability to translate requirements into end-to-end designs for systems that involve multiple interfaces and support data repositories Strong customer service skills, teaming skills, and the More ❯

expertise with Talend and Snowflake Solid knowledge of ETL tools and data transformation techniques (JSON, XML) Proficiency in SQL, Python, or other scripting languages for automation Strong understanding of metadata structures, relational databases, and data modeling Hands-on experience with version control and CI/CD practices Excellent analytical and problem-solving skills Strong communication skills and ability to work 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 ❯

6+ years of experience with data analytics, data engineering, statistical analysis, or artificial intelligence and machine learning • Experience developing and documenting organizational standards for Data Storage, Data Transformation, and Metadata Management • Ability to work independently with minimal oversight and direction • Bachelor's degree in computer sciences, information systems, engineering, or other related technical discipline. Employees of Agile Defense are our More ❯

and unstructured data sources from APIs and databases, including through R, Python, or SQL • 2+ years of experience developing and documenting organizational standards for Data Storage, Data Transformation, and Metadata Management • Experience with ETL processing • Bachelor's degree in computer sciences, information systems, engineering or other related technical discipline. WORKING CONDITIONS Environmental Conditions • Contractor site with varied travel possible. Possible More ❯

technical and business stakeholders to ensure shared understanding and effective solutions. Main duties of the job Accountabilities Work with the engineering team to implement enterprise data models, pipelines, and metadata management Collaborate with business, product, and engineering teams to understand data needs and translate them into functional data products, aligning our data architecture with wider organisational digital strategies and priorities … tasks. Advanced database manipulation and administration skills, particularly T-SQL, Azure SQL, as well as capacity with unstructured and unlinked data management languages. Experience using and implementing schema and metadata design (e.g., star schema, snowflake, normal forms), with strong understanding of master and reference data management. Experience working with Azure/GCP building and managing data solutions such as data … visualisation, APIs, including understanding and application of good practice in these areas Evidence of developing and delivering effective data engineering projects, including data architecture, data modelling, ETL processes, and metadata management concepts Evidence of using tools such as Git, GitHub and/or Azure DevOps to effectively manage work flow, version control, and collaborative development, and use of Agile delivery More ❯

and systems engineering in support of integrating model context protocol (MCP) servers. Code data pipelines using tools such as LangChain, Granite-Docling, and langextract to extract text, and images metadata and metadata definitions from data. Mapping Metadata and metadata Supporting Machine Learning and Artificial Intelligence development Designing and coding new software and/or modifying existing software to add new More ❯

experience across - TOGAF/Zachman enterprise architecture frameworks Cloud native data platforms - Azure/AWS/GCP Data mesh Data Governance Data Lakehouse, warehouse and virtualisation concepts MDM/Metadata management ETL/ELT processes and data pipeline builds Data readiness for AI Strong understanding of business architecture Be part of a team shaping the future of data-driven technology More ❯

CD pipelines and infrastructure-as-code tools (e.g., Terraform). Familiarity with ArcPy and geoprocessing services. Understanding of OGC standards (WMS, WFS, GeoJSON, etc.). Knowledge of data governance, metadata standards, and geospatial data quality assurance. Experience working in Agile development teams or DevOps environments. CLEARANCE: TS/SCI with CI Polygraph minimum More ❯

and standards to ensure data quality from source to consumption. Standardise code, product, and service quality across engineering teams by implementing best practices and governance. Design and promote reusable metadata libraries and cross-business standards in collaboration with other technical disciplines. Partner with Lead Data Engineers, Data Architects, and Technologists to design and develop innovative solutions. Continually improve data engineering More ❯

and standards to ensure data quality from source to consumption. Standardise code, product, and service quality across engineering teams by implementing best practices and governance. Design and promote reusable metadata libraries and cross-business standards in collaboration with other technical disciplines. Partner with Lead Data Engineers, Data Architects, and Technologists to design and develop innovative solutions. Continually improve data engineering More ❯

knowledge of Azure Cloud Services (DataBricks, ADF, Azure SQL, CosmosDB). Proficiency in Kimball methodology and Data Vaults. Experience with MDM, data cataloguing, and lineage management. Skilled in designing metadata-driven ingestion and transformation pipelines. Proven track record in agile delivery environments (SCRUM, PRINCE2, Lean). Excellent communication skills-able to bridge technical and non-technical audiences. Passion for emerging More ❯

knowledge of Azure Cloud Services (DataBricks, ADF, Azure SQL, CosmosDB). Proficiency in Kimball methodology and Data Vaults. Experience with MDM, data cataloguing, and lineage management. Skilled in designing metadata-driven ingestion and transformation pipelines. Proven track record in agile delivery environments (SCRUM, PRINCE2, Lean). Excellent communication skills-able to bridge technical and non-technical audiences. Passion for emerging More ❯

knowledge of Azure Cloud Services (DataBricks, ADF, Azure SQL, CosmosDB). Proficiency in Kimball methodology and Data Vaults. Experience with MDM, data cataloguing, and lineage management. Skilled in designing metadata-driven ingestion and transformation pipelines. Proven track record in agile delivery environments (SCRUM, PRINCE2, Lean). Excellent communication skills-able to bridge technical and non-technical audiences. Passion for emerging More ❯

and standards to ensure data quality from source to consumption. Standardise code, product, and service quality across engineering teams by implementing best practices and governance. Design and promote reusable metadata libraries and cross-business standards in collaboration with other technical disciplines. Partner with Lead Data Engineers, Data Architects, and Technologists to design and develop innovative solutions. Continually improve data engineering More ❯