We are partnering with a top-tier Global Financial Data & Market Intelligence Enterprise to find a Lead Azure Data Architect for their expanding technology hub.
This is a high-impact, founding-level role. You will be the sole Data Engineering domain expert within an 8-person regional team, tasked with taking IT delivery in-house from 3rd-party vendors. You will architect the transition from legacy systems to modern cloud architectures and present your strategies directly to global C-suite executives.
- Experience: 3+ Years of hands-on experience
- Work Eligibility: Malaysian Citizens, MyPR Holders, or RP-T Holders (No visa sponsorship available)
- Enterprise Architecture: Architect and build end-to-end cloud data solutions, spearheading the migration from legacy/Excel-based processes to modern Microsoft Fabric and Azure Data Factory environments.
- Vendor Handover & IT Delivery: Lead the transition of technical delivery from 3rd-party IT vendors to an internal IT delivery model.
- Stakeholder Management: Present, defend, and align architectural processes directly with global executive stakeholders, including Senior Directors, VPs, and the CFO (UK/US).
- Cloud Infrastructure: Design, deploy, and govern secure Azure infrastructure and establish scalable Infrastructure as Code (IaC) standards.
- Team Leadership: Act as the foundational Data SME, mentoring and upskilling the current 8-person local squad in data engineering best practices, with a clear path to becoming a Team Lead.
- Proven background in Enterprise Architecture, Lead Data Engineering, or Platform Strategy.
- Extensive, hands-on technical depth in Microsoft Fabric and Azure Data Factory (ADF).
- Experience designing cloud infrastructure (Terraform/Bicep, Landing Zones, Azure Networking).
- Exceptional English communication skills with a demonstrated ability to grasp complex business objectives and manage non-technical senior stakeholders.
- A true self-starter capable of operating autonomously without a senior technical mentor on-site.
- Bonus Skills: Hands-on experience with AI/ML workloads or integrations.