Technology Consultant – Cloud Data & AI Solutions

ZS is a place where passion changes lives. As a management consulting and technology firm focused on improving life and how we live it, we transform ideas into impact by bringing together data, science, technology and human ingenuity to deliver better outcomes for all. Here you’ll work side-by-side with a powerful collective of thinkers and experts shaping life-changing solutions for patients, caregivers and consumers, worldwide. ZSers drive impact by bringing a client-first mentality to each and every engagement. We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business. Bring your curiosity for learning, bold ideas, courage and passion to drive life-changing impact to ZS.

ZS’s Supply Chain & Manufacturing group helps our clients to drive higher product availability at lower costs (stock-outs, carrying costs, and supply chain operating costs) and lower environmental impact through leveraging analytics, automation and process re-design approaches. Our offerings span the spectrum of strategy, advanced analytics, planning and technology to optimize deployment of resources (inventory, network, etc.) while maintaining customer service levels.

ZS is seeking a Technology Consultant – Cloud Data & AI Solutions to support advisory, architecture, and implementation work across Supply Chain and Manufacturing clients.

In this role, you will help clients assess their current data, AI, and technology ecosystems; identify gaps and investment opportunities; and define practical roadmaps for modernization. You may support engagements such as evaluating an organization’s AI engineering strategy, designing a future-state Databricks architecture, planning cloud or data platform migrations, or helping supply chain teams use modern data and AI capabilities to improve planning, operations, and decision-making.

This role is ideal for a consultant or solution engineer who enjoys working at the intersection of business, architecture, and hands-on technology delivery. You do not need to be an expert in every platform, but you should bring strong engineering fundamentals, experience with modern cloud or data platforms, and the ability to learn quickly in complex client environments.

What You’ll Do

• Assess clients’ current data, AI, and digital technology ecosystems to identify gaps, risks, and modernization opportunities.
• Support development of AI engineering, data platform, and cloud modernization strategies.
• Translate business priorities across supply chain and manufacturing functions into scalable technical roadmaps and architecture recommendations.
• Design future-state architectures for modern data platforms, including lakehouse, warehouse, data pipeline, and analytics environments.
• Support cloud and data platform migrations, including migration planning, architecture design, platform evaluation, and implementation roadmaps.
• Help clients evaluate technologies such as Databricks, Snowflake, AWS, Azure, and emerging GenAI platforms based on business needs, scalability, cost, and long-term fit.
• Partner with business, IT, data, and operations stakeholders to align technical solutions with supply chain and manufacturing objectives.
• Lead or support implementation teams delivering data pipelines, platform components, integrations, and AI-enabled solutions.
• Bring structure to ambiguous client problems by developing assessments, recommendations, business cases, roadmaps, and executive-ready materials.
• Collaborate with global ZS teams to ensure strong delivery, project quality, and client satisfaction.

What You’ll Bring

• 5–8 years of experience in technology consulting, solution architecture, data engineering, cloud implementation, or data platform delivery.
• Experience assessing or designing data, analytics, AI, or cloud solutions in complex enterprise environments.
• Hands-on experience with at least one major cloud or data platform, such as Databricks, AWS, Azure, Snowflake, or Google Cloud.
• Exposure to AI engineering, GenAI platforms (like Azure OpenAI, OpenAI APIs, AWS Bedrock, Anthropic Claude, Google Gemini, Databricks Mosaic AI, or Snowflake Cortex), ML platforms, or AI/ML lifecycle practices.
• Experience with CI/CD, DevOps, Infrastructure as Code, observability, or release governance.
• Understanding of modern data architecture c…