DataBricks Architect

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We are seeking a forward-thinking Databricks Architect to lead the adoption and integration of Databricks as our enterprise AI/ML platform. This individual will establish the technical architecture, drive innovation, and ensure seamless collaboration with internal infrastructure teams to align with organizational standards.

The opportunity:

·       Hybrid: In office/remote

·       Architecture Leadership: Design, implement, and optimize scalable, secure, and compliant Databricks-based AI/ML architectures that support advanced analytics, data engineering, and machine learning workloads.

·       Collaboration & Compliance: Partner with internal infrastructure, security, and compliance teams to ensure all solutions meet organizational standards and regulatory requirements, including data sovereignty and global deployment needs.

·       Data Integration: Architect and implement robust integrations with diverse internal and external data sources, enabling efficient data ingestion, transformation, and access for analytics and AI/ML workflows.

·       Self-Service Enablement: Develop frameworks, tools, and documentation to enable data scientists and analysts to develop, train, and deploy models independently, fostering a culture of self-service and innovation.

·       ModelOps Strategy: Develop and implement a comprehensive ModelOps strategy to manage model lifecycle, governance, versioning, and deployment at scale. Ensure seamless integration with existing DevOps and DataOps practices623.

This position description identifies the responsibilities and tasks typically associated with the performance of the position. Other relevant essential functions may be required.

What you need:

·       Proven Experience: 5+ years architecting and implementing enterprise-grade data and AI/ML solutions, preferably with Databricks, Apache Spark, and cloud platforms (AWS, Azure, GCP).

·       Technical Expertise: Deep understanding of data Lakehouse architectures, ETL/ELT pipelines, data governance, and security best practices.

·       ModelOps Strategy: Demonstrated experience in developing and implementing a ModelOps strategy, including model lifecycle management, versioning, governance, and deployment automation.

·       Consulting & Communication: Strong consulting, stakeholder management, and communication skills, with a track record of influencing senior leadership and driving technology adoption.

·       Innovation & Initiative: Demonstrated ability to drive innovation, introduce contemporary practices, and lead technology transformations.

·       Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent experience. Desirable Attributes

·       Thought Leadership: Ability to define and communicate architecture vision, roadmaps, and best practices to both technical and non-technical audiences.

·       Continuous Improvement: Passion for learning, sharing knowledge, and staying ahead of industry trends in data and AI.

·       Customer Focus: Commitment to delivering measurable business value and exceptional user experiences