26 to 50 of 135 Remote Metadata Jobs

data architecture standards and best practices Collaborate with cross-functional teams to align data models with business needs Lead data integration, transformation, and migration strategies Maintain enterprise data models, metadata repositories, and data lineage documentation Optimise data products for performance, scalability, and reliability Skills & Experience: 10+ years in data architecture and modelling Expertise in dimensional modelling, 3NF, and Data Vault More ❯

play a key role in transforming business requirements into scalable and insightful reporting and dashboard solutions. Role The Oracle BI Consultant will design and develop OBIEE dashboards, reports, and metadata models (RPD). Translate business requirements into technical specifications and BI solutions. Write, optimise, and maintain complex SQL queries for data extraction, transformation, and analysis. Develop and manage data models More ❯

play a key role in transforming business requirements into scalable and insightful reporting and dashboard solutions. Role The Oracle BI Consultant will design and develop OBIEE dashboards, reports, and metadata models (RPD). Translate business requirements into technical specifications and BI solutions. Write, optimise, and maintain complex SQL queries for data extraction, transformation, and analysis. Develop and manage data models More ❯

tables, and scalability best practices It will also help you to have Experience establishing and enforcing data governance standards through technical architecture (not just documentation) Familiarity with data cataloging, metadata management, and observability tools A systems-thinking mindset-you understand the full data lifecycle and how to maintain integrity from source to dashboard At Booksy, we believe in the power More ❯

machine learning code to meet specific needs. Data Engineering: Ensure efficient data flow between databases and backend systems. MLOps : Automate ML workflows, focusing on testing, reproducibility, and feature/metadata storage. ML Architecture Design: Create machine learning architectures using Google Cloud tools and services. Engineering Software for Production: Build and deploy production-grade software for machine learning and data-driven More ❯

and best practices Collaborating with engineers, architects, and stakeholders to align data models with business needs Leading on data integration, transformation, and migration strategies Owning enterprise data models, dictionaries, metadata, and lineage Optimising for performance, scalability, and compliance What we’re looking for: 10+ years in data architecture and modelling Deep experience with 3NF, dimensional, and Vault 2.0 modelling Real More ❯

and best practices Collaborating with engineers, architects, and stakeholders to align data models with business needs Leading on data integration, transformation, and migration strategies Owning enterprise data models, dictionaries, metadata, and lineage Optimising for performance, scalability, and compliance What we’re looking for: 10+ years in data architecture and modelling Deep experience with 3NF, dimensional, and Vault 2.0 modelling Real More ❯

Architecture, and its roadmap; youll provide advisory and governance support to ensure projects align to simplification strategy and comply with data standards while promoting and supporting effective data modelling, metadata management and alignment to enterprise data model and data controls. Well look to you to influence the development of business strategies at an organisational level, identifying transformational opportunities for our 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 ❯

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 ❯

Governance Engineer to join our Security Team. What You Will Be Doing: Implement Technical Controls: Build and maintain a centralized data inventory, business glossary, and data mapping framework using metadata management and data catalog tools. Automate data classification, lineage tracking, and policy enforcement through scripts, APIs, and orchestration tools (e.g., dbt, Airflow). Map & Visualize Data Flows : Design and maintain More ❯

and visualise enriched data. Improve pipeline observability, validation, and fault tolerance for production-grade robustness. Enable LLM-driven workflows by shaping data to be AI-consumable (e.g. chunking, embeddings, metadata). Reduce tech debt and simplify orchestration across Flyte, Databricks, and Azure-based infrastructure. Example Projects: Design and optimise distributed data pipelines to handle large-scale video and image data More ❯

monitoring to ensure high availability and traceability. AI & Advanced Analytics Integration: Collaborate with AI/ML teams to enable model training pipelines with robust and reliable data access. Leverage metadata and structured data modeling to support AI model explainability and audit trails. Guide engineering teams on best practices for cloud-based data handling, Terraform, and secure service architecture. Coach junior More ❯

usage Support analytics and self-service reporting initiatives Skills & Experience Strong experience with GCP, BigQuery, Dataflow Proficiency in Python and Terraform Skilled in ETL/ELT, data modelling, and metadata management Familiarity with CI/CD, DevOps, and Infrastructure-as-Code Knowledge of insurance data and KPIs is advantageous but not essential Benefits: Competitive salary and benefits Discretionary bonus Hybrid More ❯

usage Support analytics and self-service reporting initiatives Skills & Experience Strong experience with GCP, BigQuery, Dataflow Proficiency in Python and Terraform Skilled in ETL/ELT, data modelling, and metadata management Familiarity with CI/CD, DevOps, and Infrastructure-as-Code Knowledge of insurance data and KPIs is advantageous but not essential Benefits: Competitive salary and benefits Discretionary bonus Hybrid More ❯

Architecture, and its roadmap; youll provide advisory and governance support to ensure projects align to simplification strategy and comply with data standards while promoting and supporting effective data modelling, metadata management and alignment to enterprise data model and data controls. Well look to you to influence the development of business strategies at an organisational level, identifying transformational opportunities for our More ❯

Data Culture & Self-Service: Support the rollout of BI tooling and self-serve capabilities across the business. Data Quality: Work closely with Data Governance to strengthen data management, including metadata and lineage, and drive data management automation. Impactful Data: Contribute to a strong data culture within Atom, ensuring the quality of BI and reporting for a rapidly growing business What 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 ❯

doing: Developing and maintaining the Enterprise Data Architecture and blueprints aligned to business goals and operational needs. Using Retail Industry Data Models, define relevant standards for data designs, models, metadata, contracts and data quality. Designing conceptual and logical data models to support business applications, repositories and data movement. Leading the design and overseeing the implementation of our strategic data platforms More ❯

doing: Developing and maintaining the Enterprise Data Architecture and blueprints aligned to business goals and operational needs. Using Retail Industry Data Models, define relevant standards for data designs, models, metadata, contracts and data quality. Designing conceptual and logical data models to support business applications, repositories and data movement. Leading the design and overseeing the implementation of our strategic data platforms More ❯