Data Design Lead

Job description

Job Tittle : Data Design Lead In this role, you will define and enforce data standards and policies, ensuring they are consistently applied across the organization. As the key accountable owner for the creation and maturity of data assets in your domain, you will oversee their progression from initial development through to operational maturity. You will also facilitate the Data Asset Owners, guiding them through the data maturity steps and ensuring that the data assets remain of high quality. Key Responsibilities: Data Asset Planning: Plan, and manage data assets and their related data pipelines in alignment with business goals. Create and manage the roadmap for data assets, ensuring that each asset aligns with business dependencies and long-term strategic goals. End-to-End Data Asset Creation: Facilitate the creation process of data assets from ideation to deployment, ensuring smooth progress and maturing of data assets according to the organizational roadmap and business priorities. Data Asset Oversight: Support the Data Asset Owners to provide oversight and guidance, ensuring that data asset development aligns with business requirements and data governance standards. Data Lineage Management: Ensure end to end traceability of data assets, enabling clear visibility to the sources, transformations and consuming applications for compliance, governance and troubleshooting purposes. Documentation Accountability: Ensure comprehensive documentation of data assets, including their tools, processes, systems and any other necessary technical documents throughout the asset creation. Data Accessibility and Consistency: Establish and maintain a central single source of truth for data assets, ensuring consistent use and accessibility of curated data from technical perspective. Set Data Standards: Define, implement, and enforce data subject area standards and policies to ensure consistent, high-quality data across the organization. Align these standards with business requirements and regulatory compliance. Cross-System Data Strategy: Lead the definition and design of a cross-system data strategy, balancing data granularity and integration requirements to meet the diverse needs of different business units and systems. Data Change Management: Build a change management plan to ensure accurate and timely updates to data assets. Regularly assess and remove obsolete data to maintain data quality and compliance with company standards. Key Skills: Leadership: Establish strong leadership over data accountability for business domains, driving data governance policies and ensuring quality data becomes a core business asset. Business Acumen and Data Modeling: Combine business insight with a strong data modeling background to develop data assets that support key business processes and strategies. Analytical and Strategic Thinking: Demonstrate robust analytical skills and strategic thinking to make impactful decisions in the creation of data assets. Financial Acumen: Apply financial acumen to optimize the cost and efficiency of data creation, ensuring that resources are used effectively and that data management efforts are cost-efficient. Minimum Qualifications: Education: University bachelor’s degree in a scientific field with two years of related experience in system application management (preferably in a healthcare related industry) Technical Skills: Strong proficiency in data modeling, data architecture and data pipeline creation. Expertise in SQL, Data Modeling, Python, Databricks, Microsoft Azure, Project Management Tools ( Jira Confluence), Agile methodology and Visualisation Tools (Power BI, Tableau) Collaboration: Proven ability to collaborate with business teams and IT stakeholders to gather requirements, manage data, and deliver value-driven solutions. Problem-Solving: Strong ability to analyze complex data challenges, apply critical thinking, and provide actionable solutions. Communication: Excellent communication skills, with the ability to present complex data concepts in a clear, understandable way to both technical and non-technical stakeholders. Preferred Qualifications: Knowledge of Good Practices (GxP) and Data Privacy standards Knowledge of Data Governance frameworks, standards and best practices (e.g. DAMA-DMBOK, ISO 8000) Familiarity with Data Governance tools like Collibra, Oval Edge a plus