21 of 21 Metadata Jobs in the South West

patterns, event-driven architectures, ETL/ELT processes, and stream processing solutions Translate business requirements into technical specifications and actionable solution designs Work with metadata management and data governance tools such as Cloud Data Catalog, Collibra, or Dataplex Build data quality alerting and data quarantine solutions to ensure downstream reliability ...

patterns, event-driven architectures, ETL/ELT processes, and stream processing solutions Translate business requirements into technical specifications and actionable solution designs Work with metadata management and data governance tools such as Cloud Data Catalog, Collibra, or Dataplex Build data quality alerting and data quarantine solutions to ensure downstream reliability ...

patterns, event-driven architectures, ETL/ELT processes, and stream processing solutions Translate business requirements into technical specifications and actionable solution designs Work with metadata management and data governance tools such as Cloud Data Catalog, Collibra, or Dataplex Build data quality alerting and data quarantine solutions to ensure downstream reliability ...

data, people, and process .Your responsibilities will include: Supporting the implementation of data governance frameworks, standards, and policies Helping maintain data definitions, glossaries, metadata, and data catalogues Engaging with stakeholders to understand data issues and support improvements Assisting with data quality assessments and remediation activities Supporting data classification, access control ...

Investigating data issues and providing clear, actionable insights Delivering core data management artefacts including: Data glossaries Data quality rules and controls Data lineage and metadata documentation Supporting data governance, records management and regulatory compliance (including GDPR) Essential Skills & Experience Data Analysis & Requirements Strong experience gathering and documenting business and technical … with unstructured data and records management tools (e.g. Microsoft Purview) Experience defining and enforcing data quality rules Experience implementing or maintaining data lineage and metadata solutions (e.g. Collibra, Solidatus) Strong understanding of regulatory and compliance requirements within financial services SQL & Reporting Strong SQL skills for data analysis, validation and reporting ...

Designing, supporting, and guiding the upgrade, management, decommissioning, and archiving of data in line with data policy Defining and maintaining data technology architecture, including metadata, integration, BI, and data warehouse architectures Producing, maintaining, and reverse-engineering data models to meet organisational and programme needs Providing input into and maintaining data … dictionaries and metadata repositories Undertaking data profiling and source system analysis to support effective data use Ensuring data solutions comply with governance, security, and assurance requirements Monitoring compliance with data standards and assessing the impact of breaches Supporting multidisciplinary delivery teams with clear data insights and architectural guidance Communicating effectively ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...

development of AI solutions using Computer Vision, Machine Learning, Generative AI, and data science to enable capabilities such as automated sports metadata generation and detection of key events in live content and data streams. Generate actionable insights for player performance, contextual statistics, and injury risk by designing models with embedded … modern ML techniques, including Generative AI, and how emergent models can extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. ...