1 to 25 of 351 Metadata Jobs

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 ❯

Models using Data Vault and Dimensional modelling methods Implement automated, reusable and efficient batch data pipelines and streaming data pipelines Work closely with Governance and Quality teams to ensure metadata, catalogue, lineage and known solutions to data issues are optimised Work closely with other data specialists and technicians in the organisation, such as Actuarial and Finance, to help with their More ❯

Lead the design and implementation of data models, pipelines, and integration frameworks. Support the implementation of Customer Data Platforms (CDPs), MDM, and CRM systems. Ensure compliance with data governance, metadata standards, and data quality frameworks. Collaborate with stakeholders to define data architecture vision and roadmap. Contribute to the development of reusable architecture assets and design patterns. Mentor junior team members More ❯

on strategic, cross-functional data initiatives with C-level stakeholders. Familiarity with cloud data platforms (e.g., Azure, AWS, GCP, Snowflake). Knowledge of data governance standards, regulatory compliance, and metadata management. Experience with BI and visualization tools such as Power BI, Tableau, or Looker. Certification in data science, analytics, or cloud technologies (e.g., Microsoft, AWS, Google). Why join Genpact More ❯

on strategic, cross-functional data initiatives with C-level stakeholders. Familiarity with cloud data platforms (e.g., Azure, AWS, GCP, Snowflake). Knowledge of data governance standards, regulatory compliance, and metadata management. Experience with BI and visualization tools such as Power BI, Tableau, or Looker. Certification in data science, analytics, or cloud technologies (e.g., Microsoft, AWS, Google). Why join Genpact More ❯

into technical specifications and ensure timely delivery of data products. 4. Data Quality & Governance Implement monitoring systems to ensure data accuracy, completeness, and timeliness. Support data governance initiatives, including metadata management, lineage tracking, and access controls. Ensure compliance with regulatory standards (e.g., REMIT, EMIR) and internal audit requirements. 5. Innovation & Continuous Improvement Evaluate and adopt new technologies (e.g., streaming platforms More ❯

emerging technologies, and market trends, advising leadership on best practices. • Communicate effectively with end-users, support staff, management, and other departments on all data-related initiatives. • Establish and maintain metadata management, data lineage, and cataloging to enhance discoverability and usability across the organization. • Assist other teams with the integration, implementation, and troubleshooting of projects involving local, cloud, and hybrid network More ❯

/or Scala. * Expertise in ETL/ELT processes, data warehousing, and data mesh architectures. * Familiarity with AI/ML concepts and their application in data analytics. * Experience with metadata management, data lineage tracking, and data cataloguing. * Knowledge of serverless data processing, event-driven architectures, and modern data stacks. In accordance with the Employment Agencies and Employment Businesses Regulations More ❯

engagement capabilities. Nice to Have Familiarity with data visualization tools (e.g., Power BI, Tableau). Exposure to cloud platforms (e.g., Databricks , Snowflake ). Understanding of data governance , lineage , and metadata management . Experience with data cataloguing and quality frameworks . More ❯

organisational skills and attention to detail. Preferred Qualifications Microsoft Azure Data Engineer certification. Experience with Azure Synapse Analytics and Power BI. Familiarity with data governance, data quality frameworks, and metadata management. Key Behaviours & Competencies Personal Drive – Resilient and committed to achieving goals through persistent effort. Innovation – Generates new ideas and solutions through original thinking. Results Focus – Aligns team efforts with More ❯

organisational skills and attention to detail. Preferred Qualifications Microsoft Azure Data Engineer certification. Experience with Azure Synapse Analytics and Power BI. Familiarity with data governance, data quality frameworks, and metadata management. Key Behaviours & Competencies Personal Drive - Resilient and committed to achieving goals through persistent effort. Innovation - Generates new ideas and solutions through original thinking. Results Focus - Aligns team efforts with More ❯

discovery, evaluating source systems and APIs, and creating stories for implementation Collaborate with third parties to ensure interoperability and integration compatibility Champion best practices in warehousing techniques (e.g. Kimball), metadata management, and performance optimisation Support delivery through integration testing, reconciliation, and reporting visualisation (e.g. Power BI, Tableau) About You: Proven experience designing data architectures for large-scale platforms and diverse More ❯

discovery, evaluating source systems and APIs, and creating stories for implementation Collaborate with third parties to ensure interoperability and integration compatibility Champion best practices in warehousing techniques (e.g. Kimball), metadata management, and performance optimisation Support delivery through integration testing, reconciliation, and reporting visualisation (e.g. Power BI, Tableau) About You: Proven experience designing data architectures for large-scale platforms and diverse More ❯

discovery, evaluating source systems and APIs, and creating stories for implementation Collaborate with third parties to ensure interoperability and integration compatibility Champion best practices in warehousing techniques (e.g. Kimball), metadata management, and performance optimisation Support delivery through integration testing, reconciliation, and reporting visualisation (e.g. Power BI, Tableau) About You: Proven experience designing data architectures for large-scale platforms and diverse More ❯

discovery, evaluating source systems and APIs, and creating stories for implementation Collaborate with third parties to ensure interoperability and integration compatibility Champion best practices in warehousing techniques (e.g. Kimball), metadata management, and performance optimisation Support delivery through integration testing, reconciliation, and reporting visualisation (e.g. Power BI, Tableau) About You: Proven experience designing data architectures for large-scale platforms and diverse More ❯

discovery, evaluating source systems and APIs, and creating stories for implementation Collaborate with third parties to ensure interoperability and integration compatibility Champion best practices in warehousing techniques (e.g. Kimball), metadata management, and performance optimisation Support delivery through integration testing, reconciliation, and reporting visualisation (e.g. Power BI, Tableau) About You: Proven experience designing data architectures for large-scale platforms and diverse More ❯

discovery, evaluating source systems and APIs, and creating stories for implementation Collaborate with third parties to ensure interoperability and integration compatibility Champion best practices in warehousing techniques (e.g. Kimball), metadata management, and performance optimisation Support delivery through integration testing, reconciliation, and reporting visualisation (e.g. Power BI, Tableau) About You: Proven experience designing data architectures for large-scale platforms and diverse More ❯

APIs, and machine learning models in coordination with DevOps teams. Define and embed best practices for data warehousing and Lakehouse architecture (e.g. Medallion). Standardise data development, modelling, and metadata management across the enterprise. Implement lineage tracking and orchestration tools to improve transparency and governance. Conduct code reviews, testing, and documentation to ensure quality and robustness of analytics outputs. Take More ❯

meetings 2. Data Governance & Quality: Establish and enforce data governance policies, standards, and procedures Define data quality rules and implement processes for data validation and cleansing Design and implement metadata management strategies Architect secure data storage, access controls, and data privacy measures Develop and implement Master Data Management (MDM) strategies Partner closely with the Enterprise Architect, Integration Architect, business stakeholders More ❯

Data Strategy Define and lead enterprise wide data strategy Design and maintain a scalable, secure data architecture Deep understanding of Data Governance, Modern data platforms: Cloud Data quality Management, metadata, lineage and data modelling Experience with Data integration, master data management (MDM) and designing scalable data pipelines Data Privacy, regulatory compliance, and security best practises BI Tools Power BI, Tableau More ❯

Data Strategy Define and lead enterprise wide data strategy Design and maintain a scalable, secure data architecture Deep understanding of Data Governance, Modern data platforms: Cloud Data quality Management, metadata, lineage and data modelling Experience with Data integration, master data management (MDM) and designing scalable data pipelines Data Privacy, regulatory compliance, and security best practises BI Tools Power BI, Tableau More ❯

transactional, analytical, and operational systems Architect solutions for data lakes, warehouses, and master data management (MDM) Establish reference architecture for data ingestion, transformation, storage, and consumption Champion data quality, metadata, and governance standards (including GDPR compliance) Provide architectural oversight on multi-cloud and hybrid environments Collaborate with stakeholders to enable data-driven decision-making and new revenue streams Skills & Experience More ❯

engagement, and ensure alignment across business, IT, compliance, and security teams. Establish data quality metrics, rules, and monitoring mechanisms across cloud data pipelines and lakehouses. Champion the use of metadata management, data catalogs (e.g., Azure Purview, Unity Catalog), and standardized business glossaries. Provide governance oversight for data sharing and consumption in Databricks notebooks, Power BI reports, and machine learning workflows. More ❯

data from SAP (e.g., S/4HANA, BW/4HANA) and non-SAP sources (e.g., cloud platforms, APIs, third-party systems). Establish and enforce data governance policies including metadata management, data lineage tracking, and access control to ensure data integrity and compliance. Optimize data pipelines and transformation logic using SAP Datasphere's capabilities to support real-time and batch More ❯

Governance and Quality Assurance: Embed governance, security, and data quality practices into engineering workflows. Define guardrails and reference implementations for data access control, data lineage, and compliance. Promote consistent metadata management and enforce technical standards to ensure trust in data assets. Stakeholder Engagement: Collaborate with PN D&A leadership, PN product owners, and segment D&A leadership to synchronize and More ❯