Data Design Lead

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