76 to 100 of 371 Metadata Jobs

with analysts and business teams to align data models with reporting, AI, and automation needs. You'll also contribute to the adoption of CI/CD, version control, and metadata-driven practices that enhance scalability and trust in analytics outputs. This is a hands-on role where technical precision and design thinking come together to enable a data-first culture. More ❯

with analysts and business teams to align data models with reporting, AI, and automation needs. You'll also contribute to the adoption of CI/CD, version control, and metadata-driven practices that enhance scalability and trust in analytics outputs. This is a hands-on role where technical precision and design thinking come together to enable a data-first culture. More ❯

growth and ensuring succession planning. Knowledge: * Profound understanding of data management principles, methodologies, and best practices. * Familiarity with data analytics tools, techniques, and technologies. * Strong understanding of data architecture, metadata management, and data quality techniques * Knowledge of project management methodologies, such as Agile, Scrum, or Waterfall. * Understanding of business intelligence concepts and practices. * Awareness of regulatory requirements related to data 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 ❯

solutions for our most strategic customers—whether next-generation innovations or custom-tailored adaptations. Take ownership of the full problem space, spanning data storage and pipelines through to APIs, metadata, and UIs Improve and extend existing products with new features, cost optimizations, and reliability enhancements, while addressing technical debt and ensuring alignment with the broader architecture. Required Qualifications: 5+ years More ❯

user needs when designing deliverables. Experience in designing technology solutions with complex end-to-end data flows. Experience in implementing data governance, including data cataloging, data lineage tracking, and metadata management to ensure data accuracy, accessibility, and compliance. Preferred: Experience with Databricks Understanding of how data platforms interact with marketing and customer engagement platforms. Knowledge of service-oriented architecture, including More ❯

user needs when designing deliverables. Experience in designing technology solutions with complex end-to-end data flows. Experience in implementing data governance, including data cataloging, data lineage tracking, and metadata management to ensure data accuracy, accessibility, and compliance. Preferred: Experience with Databricks Understanding of how data platforms interact with marketing and customer engagement platforms. Knowledge of service-oriented architecture, including More ❯

Streams & Tasks, and performance optimization Integration with AWS services and orchestration tools Expertise in data integration patterns, ETL/ELT, and data pipeline orchestration Experience with data quality frameworks, metadata management, and data lineage Hands-on experience with machine learning pipelines and generative AI engineering Familiarity with DevOps practices, CI/CD for data workflows, and infrastructure-as-code (e.g. More ❯

Streams & Tasks, and performance optimization Integration with AWS services and orchestration tools Expertise in data integration patterns, ETL/ELT, and data pipeline orchestration Experience with data quality frameworks, metadata management, and data lineage Hands-on experience with machine learning pipelines and generative AI engineering Familiarity with DevOps practices, CI/CD for data workflows, and infrastructure-as-code (e.g. More ❯

relevance to business needs. Develop Databricks notebooks to deliver analytical insights and support strategic business decisions, ensuring transparency and reproducibility of analysis. Demonstrate expertise in SQL, Spark, PySpark, Python, metadata management, and translate complex analytics into actionable business intelligence. Work Location Various unanticipated work locations throughout the United States; relocation may be required. Must be willing to relocate. Requirements Master More ❯

standards and privacy regulations (HIPAA, PHI). Participate in code reviews, documentation, and team retrospectives to continuously improve data quality and engineering practices. Contribute to internal data governance and metadata management initiatives. Experience: 5+ years of professional experience in data engineering, analytics engineering, or related roles. Hands-on experience with dbt (Data Build Tool) in a production environment. Strong SQL 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 ❯

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 ❯

/LODs, and voxel/point-cloud conversions. Implement labeling and QA workflows, manage external annotation vendors, and automate quality checks to ensure scalable, reliable datasets. Define schemas and metadata for digital assets, maintaining catalogues, lineage, and versioning to ensure reproducibility and governance. Enforce data quality, drift detection, and compliance (GDPR/COPPA), including watermarking and traceability to safeguard IP More ❯

/LODs, and voxel/point-cloud conversions. Implement labeling and QA workflows, manage external annotation vendors, and automate quality checks to ensure scalable, reliable datasets. Define schemas and metadata for digital assets, maintaining catalogues, lineage, and versioning to ensure reproducibility and governance. Enforce data quality, drift detection, and compliance (GDPR/COPPA), including watermarking and traceability to safeguard IP More ❯

and dialogue annotation, tailored for NLP enrichments across communication products. Shape and evolve schematic structures and data models that serve as the foundation for annotation quality and reuse. Define metadata structures and enrichment tags that help interpret communication context, intent, and relevance to user queries. Collaborate with ML engineers and product stakeholders to align annotation efforts with model requirements and More ❯

work with a range of structured, semi-structured and unstructured file formats including Parquet, json, csv, xml, pdf, jpg. Tools and methods to develop comprehensive data reliability and active metadata solutions. Ability to work with and develop APIs (including data transformations). Ability to deliver data deidentification and anonymisation solutions. Understanding of Cloud security frameworks (specifically on the AWS Cloud More ❯

in designing and delivering modern data solutions to support advanced analytics and AI-driven initiatives. Key Responsibilities & Experience: Proven expertise in data architecture , including data modelling , analysis , transformation , migration , metadata , and master data management . Track record of delivering data analytics and AI/ML-enabling solutions across complex environments. Hands-on experience with cloud data platforms , ideally AWS (S3 More ❯

and optimising scripts). Experience with AWS Athena and related data warehousing/analytics tools (e.g. Redshift). Understanding of data modelling principles — normalisation, star/snowflake schemas, and metadata management. Knowledge of both SQL and NoSQL databases. Ability to review and enhance existing data pipelines without rebuilding them. Excellent communication and documentation skills, comfortable in a technical, fast-paced 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 ❯

skills and understanding of modern data architecture principles. Hands-on experience with Tableau for enterprise-grade dashboard development. Familiarity with orchestration tools (e.g., Prefect, Airflow), data quality frameworks, and metadata tools. Proficiency in Git, CI/CD, and scripting with Python. Excellent communication skills and ability to work collaboratively across technical and business teams. More ❯

skills and understanding of modern data architecture principles. Hands-on experience with Tableau for enterprise-grade dashboard development. Familiarity with orchestration tools (e.g., Prefect, Airflow), data quality frameworks, and metadata tools. Proficiency in Git, CI/CD, and scripting with Python. Excellent communication skills and ability to work collaboratively across technical and business teams. More ❯

to align data strategies with business goals and deliver measurable value. What We're Looking For Deep Understanding of Data Management : Proven expertise in data quality, governance, security, and metadata management. Proficiency in Data Management Tools : Strong technical skills in tools like Informatica, Collibra, Talend, and Erwin. Data Modelling and Architecture : Ability to design and implement complex data models and More ❯