Description

Define and maintain enterprise data architecture principles, reference architectures, and future-state roadmaps with a strong focus on Databricks and AI enablement.

This role is on-site.

Responsibilities

• Design end-to-end data and AI architectures, including ingestion, lakehouse storage, processing, analytics, machine learning, and generative AI workflows.
• Partner with business, analytics, and technology leaders to translate strategic objectives into scalable, Databricks-based data and AI solutions.
• Lead evaluation, selection, and adoption of cloud-based data, analytics, and AI technologies, with Databricks as the core platform.
• Identify and implement automation opportunities across data pipelines, ML workflows, and AI production deployments.
• Define and implement enterprise AI and advanced analytics architectures, including hands-on exposure to ML platforms, MLOps pipelines, feature engineering, and model deployment.

Required Skills

• 12+ years of experience in enterprise data architecture and large-scale data platforms.
• Deep domain experience within customer, manufacturing, or supply chain data ecosystems.
• Proven ability to lead enterprise data and AI architecture initiatives and influence senior technical and business stakeholders.
• Strong communication skills with the ability to articulate complex data and AI concepts to executive leadership.
• Hands-on experience with Azure Databricks and GenAI technologies.
• Experience applying AI solutions across domains such as demand planning, forecasting, customer insights, intelligent manufacturing, and supply chain optimization.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

Preferred Skills

• Relevant architecture certifications (e.g., TOGAF 9, IAF, or equivalent).

Key Skills

Education

Any Graduate