Data Lead

In this Data Lead role, you will own LYNX’s data domain end-to-end, guiding the transformation from a fragmented setup to a scalable, platform-driven ecosystem. You’ll align Data Platform, Analytics, and Data Science to make data-driven decision-making the default across the company. You’ll mature the self-service platform, embed governance, and lay foundations for AI and ML. This hands-on leadership position involves building and coaching the team while collaborating with senior stakeholders to turn data into commercial value.

• competitive salary
• fixed 13th month
• 8% holiday allowance
• pension scheme fully paid by LYNX
• public transport travel allowance
• home office equipment and allowance

• Own the Data Domain End-to-End: steer strategy, architecture, governance, standards, and roadmap across Data Platform, Analytics, and Data Science
• Design structural solutions to recurring data problems and promote best practices across the organisation
• Mature the Platform & Enable Self-Service: evolve warehouse, catalog, ingestion, semantic/m red layer, and access models to support self-service data
• Raise Data Maturity: improve data capture and usage at the source, promoting data literacy and ownership
• Define the Future of Analytics: articulate AI-driven analytics vision and enable reliable data foundations for AI/ML
• Partner with Leadership on high-impact questions and deliver analyses that influence decisions
• Build & Develop the Team: onboard and coach Data Platform Engineer, Data Analytics Engineer, and Data Scientists
• Lead the Data Science Capability: develop centralised data science with a path to hybrid squad partnership
• Provide Functional Leadership to Analysts: establish standards and priorities with Engineering Managers
• Support Regulatory Reporting: ensure data platform and governance meet regulatory standards
• Set Governance Standards: establish ownership, lineage, quality, and privacy
• Lay the AI/ML Foundations: prepare platform and semantic layer for AI-assisted access and ML use cases

• Experienced data leader with hands-on architecture and transformation experience
• Strong knowledge of modern data platform architecture: warehousing, ingestion, cataloging, dbt-based modelling, semantic layers
• Understanding of Data Platform, Analytics, and Data Science to set direction across all three
• Pragmatic build-vs-buy mindset with market-standard tooling
• Strong communicator able to translate technical choices into business impact
• Leadership style focused on enabling others and delivering independent value across the organisation
• System-thinking approach to root causes and cross-department influence
• Ability to operate in a matrix organisation with cross-team alignment
• Governance, quality, and compliance as design principles

• communication
• leadership
• systems thinking
• data platform architecture
• data warehousing
• data ingestion