Data Engineering And Platform Lead

Job Description

Role Purpose

The roleis responsible forestablishingand leading the organization’s data engineering and platform capability, turning business data into reliable, governed, and reusable information. Combining hands-on technical leadership with people management, the role will shape the platform, engineering practices, data products, and service standards needed to support reporting, analytics, decision-making, automation, and AI. The role is expected to create momentum, resolve delivery barriers, and build a scalable internal capability that grows with the organization.

Key Accountabilities

• Define and deliverthe dataengineering and platform roadmap,coordinating priorities, dependencies, and capacity with the IT Portfolio Manager.
• Assess the data landscape across structured and unstructured sources, including document-based information, andestablisha clear understanding of ownership, definitions, access requirements, quality gaps, dependencies, and business importance.
• Lead the hands-on design, build, integration, and operation of secure, scalable, and reliable data pipelines, platforms, and services.
• Create reusable data products, models, and shared data capabilities that support reporting, analytics, operational needs, decision-making, automation, and AI.
• Establish engineering standards and repeatable practices for integration, development, version control, testing, documentation, release, recovery, monitoring, and support.
• Ensure data quality, integrity, consistency, freshness, lineage, security, and regulatory requirements are embedded throughout the data lifecycle.
• Own platform performance, reliability, availability, capacity, supportability, cost, technical debt, incident resolution, and continuous improvement.
• Work with IT Business Partners and business, analytics, architecture, AI, cybersecurity, and technology teams to translate requirements into reliable data solutions and measurable outcomes.
• Lead, coach, and develop team members, setting clear expectations fordeliveryquality, ownership, accountability, and proactive follow-through.
• Manage data engineering vendors and partners, ensuringdeliveryquality, knowledge transfer, sustainable support, and increasing internal ownership, while actively resolving dependencies and blockers.

Qualifications, Experience, Knowledge & Skills

• Bachelor’s degree in Computer Science, Data Engineering, Software Engineering, or a related discipline, or equivalent practical experience. Relevant professional certifications are an advantage.
• Typically8+ years in data engineering, platform delivery, software engineering, orrelatedfield.
• Proven hands-on experienceestablishingdata platforms from an early stage, including designing, building, deploying, andoperatingscalable Azure data platforms, production pipelines, and reusable data products.
• Strong experience across data integration, transformation, modeling, quality, lineage, monitoring, security, performance, resilience, and operational support.
• Experienceestablishingengineering and operational practices for version control, testing, controlled releases, documentation, monitoring, incident management, and continuous improvement.
• Experience creating governed data products and reusable information assets from structured and unstructured sources. Experience enabling the controlled use of document-based information for analytics, automation, or AI is an advantage.
• Experience leading engineers, building internal capability, managing technical delivery, and coordinating vendors and implementation partners with effective knowledge transfer.
• Hands-on leader who balances immediate delivery with long-term platform foundations.
• Proactive and accountable, withthe persistenceand judgment to keep work moving.
• Pragmatic and quality-focused, challenging weak data, unclear requirements, and unsustainable approaches.
• Clear, collaborativecommunicatoracross technical, business, and leadership audiences.
• Adaptable and outcome-driven, with a focus on building capability, operational excellence, and measurable value.

Requirements