1 to 25 of 639 Metadata Jobs

and engage with, support and lead on the finance data requirements and design for any future systems required for central financial reporting within Government and HM Treasury. Showcase excellent metadata quality management and embed effective processes and procedures in product lifecycles to drive high quality outputs and standards, utilising Project, and Programme Management methodologies, best practices, and ways of working. … dictionary https://assets.publishing.service.gov.uk/media/5b27cf2240f0b634b469fb1a/CS_Behaviours_2018.pdf This role will assess you at the Grade 7 level: Proven experience of establishing data standards, metadata management, data structures, and expertise in data analysis. Experience of Digital Solutions such as ERP (Enterprise Resource Platforms) and EPM (Enterprise Performance Management) Technology, including the best practice application of More ❯

promote the value of data across business and technology teams. Mentor data engineers, BI developers, and other stakeholders in data architecture and best practices. Maintain comprehensive architecture documentation for metadata, data lineage, and data governance. Essential Skills & Qualifications Extensive experience architecting enterprise data solutions and designing scalable data platforms. Proven expertise in data modeling (conceptual, logical, physical), metadata management, and More ❯

teams. Data Integration and Management: Design and implement robust ETL processes to integrate data from various sources into the data warehouse and big data platforms. Oversee the management of metadata, master data, and data lineage across systems. Ensure data consistency, accuracy, and availability for business users. Performance Optimization: Monitor and optimize the performance of data platforms and processes. Implement strategies More ❯

creation of company data quality foundations by developing and delivering technical solutions related: Data Governance & Management policies as code Automatic Data Observability and Quality metrics implementation, Effective and efficient Metadata Management & Data Catalogue, Data Policies and Procedures automation Data Security processes and controls automation Responsibilities: Reporting into the Head of Data Governance Office, this role will be responsible to: Design … SQL, Python, RestAPI Data Ingestion/ETL tools: Airflow; Snowpipe, or similar Data Transformation tools (SQL or python based): dbt or similar. Data management & Governance platforms: Collate/Open Metadata, Collibra, Infosphere, Montecarlo, Informatica or similar Cloud Data Visualization Tools: Tableau (preferred) or similar Git repositories: Bitbucket Cloud or similar Gitlab, Github Documentation: Atlassian Confluence or similar Soft Skills Excellent More ❯

analyzing data from various sources such as Snowflake and Palantir, ensuring effective visualization and reporting. Design, build, and manage data pipelines, including data transformation mapping, data flow diagrams, and metadata collection, to ensure data accessibility, accuracy, and security. Must have strong SQL background Document and maintain data models (Conceptual, Logical, and Physical) and metadata management solutions to facilitate efficient and More ❯

and data governance Implement data quality monitoring and alerting processes. Work with data governance teams to ensure compliance with data governance policies and standards. Implement data lineage tracking and metadata management processes. Collaboration & Communication: Collaborate closely with data scientists, economists, and other technical teams to understand data requirements and translate them into technical solutions. Communicate technical concepts effectively to both More ❯

and data governance Implement data quality monitoring and alerting processes. Work with data governance teams to ensure compliance with data governance policies and standards. Implement data lineage tracking and metadata management processes. Collaboration & Communication: Collaborate closely with data scientists, economists, and other technical teams to understand data requirements and translate them into technical solutions. Communicate technical concepts effectively to both More ❯

supporting data governance programs, including defining data policies, standards, and procedures. • Data Architecture: Familiarity with different data architectures (e.g., data warehousing, data lakes, data mesh), data modeling techniques, and metadata management. Experience working with or contributing to the design and implementation of data architectures. • Cloud Computing: Experience with cloud platforms (AWS, Azure, GCP) and their data services, including storage, compute More ❯

managing large-scale data solutions on Microsoft Azure. Unity Catalog Mastery: In-depth knowledge of setting up, configuring, and utilizing Unity Catalog for robust data governance, access control, and metadata management in a Databricks environment. Databricks Proficiency: Demonstrated ability to optimize and tune Databricks notebooks and workflows to maximize performance and efficiency. Experience with performance troubleshooting and best practices for More ❯

ensuring data quality, integrity, and security across Power BI solutions. Collaborate with theData Governance teamto maintain areport catalogue, data dictionary,and data lineage, leveraging tools likeAtaccama(or similar) for metadata management. Implement role-based access controls, manage row-level security (RLS), and adhere to data privacy regulations and internal policies. Performance Monitoring & Optimization Monitor and optimize Power BI report performance More ❯

problems. Key responsibilities: Data Platform Design and Architecture Design, develop, and maintain a high-performing, secure, and scalable data platform, leveraging Databricks Corporate Lakehouse and Medallion Architectures. Utilise our metadata-driven data platform framework combined with advanced cluster management techniques to create and optimise scalable, robust, and efficient data solutions. Implement comprehensive logging, monitoring, and alerting tools to manage the … Spark. Proven experience working with Azure data platform services, including Storage, ADLS Gen2, Azure Functions, Kubernetes. Background in cloud platforms and data architectures, such as Corporate DataLake, Medallion Architecture, Metadata Driven Platform, Event-driven architecture. Proven experience of ETL/ELT, including Lakehouse, Pipeline Design, Batch/Stream processing. Strong working knowledge of programming languages, including Python, SQL, PowerShell, PySpark … Spark SQL. Good working knowledge of data warehouse and data mart architectures. Good experience in Data Governance, including Unity Catalog, Metadata Management, Data Lineage, Quality Checks, Master Data Management. Experience using Azure DevOps to manage tasks and CI/CD deployments within an Agile framework, including utilising Azure Pipelines (YAML), Terraform, and implementing effective release and branching strategies. Knowledge of More ❯

problems. Key responsibilities: Data Platform Design and Architecture Design, develop, and maintain a high-performing, secure, and scalable data platform, leveraging Databricks Corporate Lakehouse and Medallion Architectures. Utilise our metadata-driven data platform framework combined with advanced cluster management techniques to create and optimise scalable, robust, and efficient data solutions. Implement comprehensive logging, monitoring and alerting tools to manage the … Spark. Proven experience working with Azure data platform services, including Storage, ADLS Gen2, Azure Functions, Kubernetes. Background in cloud platforms and data architectures, such as Corporate DataLake, Medallion Architecture, Metadata Driven Platform, Event-driven architecture. Proven experience of ETL/ELT, including Lakehouse, Pipeline Design, Batch/Stream processing. Strong working knowledge of programming languages, including Python, SQL, PowerShell, PySpark … Spark SQL. Good working knowledge of data warehouse and data mart architectures. Good experience in Data Governance, including Unity Catalog, Metadata Management, Data Lineage, Quality Checks, Master Data Management. Experience using Azure DevOps to manage tasks and CI/CD deployments within an Agile framework, including utilising Azure Pipelines (YAML), Terraform, and implementing effective release and branching strategies. Knowledge of More ❯

solution architects, and data product teams to gather requirements and design solutions. Provide guidance on data integration, transformation, and migration strategies. Establish and maintain enterprise data models, data dictionaries, metadata repositories, and data lineage documentation. Ensure data models comply with organizational policies and regulatory requirements. Optimize data products and their components for performance, scalability, and reliability. Evaluate and recommend data … tools like GitHub Actions or similar. AWS certifications such as AWS Certified Data Engineer. Knowledge of Snowflake, SQL, Apache Airflow, and DBT. Familiarity with Atlan for data cataloging and metadata management. Understanding of iceberg tables. Who we are: We're a global business empowering local teams with exciting work that is making a difference. Our portfolio includes consulting, applications, business More ❯

. Hands-on experience with Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for pipeline development. Deep understanding of data architecture, dimensional modelling, and metadata management. Experience with cloud platforms (AWS, GCP, or Azure). Familiarity with version control, CI/CD , and Infrastructure-as-Code (Terraform or similar). Desirable: Background in fintech or More ❯

. Hands-on experience with Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for pipeline development. Deep understanding of data architecture, dimensional modelling, and metadata management. Experience with cloud platforms (AWS, GCP, or Azure). Familiarity with version control, CI/CD , and Infrastructure-as-Code (Terraform or similar). Desirable: Background in fintech or More ❯

. Hands-on experience with Apache Airflow (or similar orchestration tools). Strong proficiency in Python and SQL for pipeline development. Deep understanding of data architecture, dimensional modelling, and metadata management. Experience with cloud platforms (AWS, GCP, or Azure). Familiarity with version control, CI/CD , and Infrastructure-as-Code (Terraform or similar). Desirable: Background in fintech or More ❯

workflows using technologies such as BigQuery, Dataflow, Informatica, or IBM DataStage, supporting both real-time and batch data processing. Governance & Data Quality Management: Establish comprehensive data governance frameworks, including metadata management and quality assurance, using platforms like Unity Catalog, Alation, Profisee, or DQ Pro. Strategic Advisory & Stakeholder Engagement: Serve as a strategic partner to executive stakeholders (e.g., CDOs, CIOs, Heads More ❯

Duck Creek, Insis, SICS, Insurity, or other legacy/modern platforms). Familiarity with ETL tools and processes used in data migration or data integration projects. Understanding data governance, metadata management, and data quality best practices. Experience in Agile, Scrum, or hybrid delivery methodologies. Knowledge of data warehousing, data visualization, and business intelligence tools. Bachelor's degree in Computer Science More ❯

supporting data governance programs, including defining data policies, standards, and procedures. • Data Architecture: Familiarity with different data architectures (e.g., data warehousing, data lakes, data mesh), data modeling techniques, and metadata management. Experience working with or contributing to the design and implementation of data architectures. • Cloud Computing: Experience with cloud platforms (AWS, Azure, GCP) and their data services, including storage, compute More ❯

data models, and pipelines in Snowflake and cloud platforms (AWS, Azure, or GCP). Develop and optimize scalable ELT/ETL processes using SQL and Python. Define data governance, metadata management, and security best practices. Collaborate with data engineers, analysts, product managers, and stakeholders to understand data needs and translate them into robust architectural solutions. Oversee data quality, lineage, and More ❯

data models, and pipelines in Snowflake and cloud platforms (AWS, Azure, or GCP). Develop and optimize scalable ELT/ETL processes using SQL and Python. Define data governance, metadata management, and security best practices. Collaborate with data engineers, analysts, product managers, and stakeholders to understand data needs and translate them into robust architectural solutions. Oversee data quality, lineage, and More ❯

data models, and pipelines in Snowflake and cloud platforms (AWS, Azure, or GCP). Develop and optimize scalable ELT/ETL processes using SQL and Python. Define data governance, metadata management, and security best practices. Collaborate with data engineers, analysts, product managers, and stakeholders to understand data needs and translate them into robust architectural solutions. Oversee data quality, lineage, and More ❯

data quality, integrity and compliance with governance policies and regulatory standards Collaborate with enterprise architects, DBAs and infrastructure teams to optimize data performance security Develop and maintain data lineage, metadata and architecture documentation Support reporting and analytics initiatives by ensuring data availability and consistency across systems Assist in designing data integration using tools such as OIC (Oracle Integration Cloud), Oracle More ❯

queries; Experience GCP Big Query is a plus Experience with GIT and GitHub version control. Extensive experience in architecture, construction, and implementation of data-intensive solutions Strong understanding of metadata management and data cataloging Adeptness to learn new assignments, technologies and applications quickly and manage multiple assignments simultaneously Ability to troubleshoot, maintain, reverse engineer and optimize existing ETL pipelines. Familiarity More ❯

modeling, both SQL and NoSQL, with expertise in distributed systems design; • Experience with distributed processing technologies and familiarity with tools like Airflow for workflow orchestration; • Knowledge of data governance, metadata management, and best practices in ensuring data quality and compliance; • Excellent communication skills and the ability to collaborate effectively in cross-functional teams; • Analytical mindset, attention to detail, and problem More ❯