Get more replies from employers
Send a job-specific resume in minutes.
Lewis Personnel Management seeks an experienced Practice Lead – Cloud & Data to shape cloud strategy and modernization efforts. You will lead high-performing teams, deliver secure, scalable solutions, and drive digital transformation with governance and FinOps best practices.
The role requires 12+ years in cloud/data, leadership, and deep expertise across AWS/Azure/GCP, with proven delivery of migration and modernization projects in enterprise settings.
We are seeking an experienced Practice Lead – Cloud & Data to lead our cloud and data practice. This role is responsible for shaping cloud strategy, driving data platform modernization, leading high-performing teams, and delivering secure, scalable solutions that support business growth and digital transformation.
Develop and execute the Cloud & Data strategy and roadmap.
Lead cloud migration, modernization, and data platform initiatives.
Promote cloud-native technologies, data engineering, analytics, and AI enablement.
Establish governance, security, performance, and cost optimization standards (FinOps).
Build and mentor cloud, platform, and data engineering teams.
Partner with business and technology leaders to deliver transformation programs.
Support pre-sales, solution design, proposals, and client presentations.
Build strategic partnerships with cloud and technology vendors.
Required
12+ years of experience in cloud, data, or platform engineering, including 5+ years in a leadership role.
Strong expertise in AWS, Azure, or GCP and modern data architectures.
Proven experience delivering cloud migration, platform modernization, or data transformation projects.
Strong leadership, stakeholder management, and communication skills.
Experience working in enterprise or regulated environments.
Preferred
Experience in consulting or digital transformation.
Knowledge of data governance, AI, MDM, or advanced analytics.
Cloud, architecture, or data engineering certifications.
Experience with FinOps and cloud cost optimization.