Senior Data Architect - AI/ML Solutions / Databricks

We began a movement when we started Resilinc in 2010 with our belief in the power of supply chain to be a force for good, to improve the lives of people and our communities. Our vision is for the world to have a place where suppliers and customers can collaborate securely with transparency and trust as the foundation. Today Resilinc’s flagship supply chain visibility, mapping and AI-powered monitoring and predictive analytics platform is widely considered the Gold Standard for resilience.

We wake up every day with the power of our important Mission driving our every action. Join our passionate, highly motivated and VIRTUAL global team that is energized and working hard to positively impact the world.

We’re seeking an innovative Senior Data Architect to design and implement our enterprise data platform, a cornerstone of our data strategy. Reporting to the Director of Data Science, the Senior Data Architect will be responsible for creating the technical foundation that supports our machine learning experiments, agentic AI workflows, and curated data sets. In this role, you will leverage Databricks as our core technology platform to build scalable, efficient data architecture that enables advanced analytics and AI capabilities across the organization.

This role offers a significant opportunity to shape the future of our data infrastructure and drive innovation through thoughtful architectural decisions. We are seeking a technically proficient leader who combines deep expertise in modern data platforms with a collaborative approach to solving complex data challenges in a growing, fast-paced environment.

What You Will Do

Strategic Architecture Design

• Reporting to the CTO, design and implement a comprehensive data architecture strategy utilizing Databricks as the primary technology platform.
• Develop architectural patterns and frameworks that support machine learning experiments, agentic AI workflows, and the creation of curated data sets.
• Define data modeling approaches, storage strategies, and processing frameworks that balance performance, cost, and scalability requirements.
• Establish data governance practices, security controls, and compliance measures within the architectural design.
• Create architectural roadmaps that align with the company’s overall data and AI strategy.
  
  
  

Technical Implementation

• Lead the technical implementation of the data platform architecture on Databricks, ensuring best practices for lakehouse architecture, Delta Lake implementation, and optimization of compute resources.
• Design and implement data pipelines that support both batch and real-time processing needs across various data sources and destinations.
• Establish efficient data ingestion patterns, transformation workflows, and data quality frameworks within the Databricks ecosystem.
• Develop architectural solutions for complex data challenges, including data versioning, feature stores for ML, and integration with AI services.
• Create reference architectures and technical documentation that guide implementation teams and ensure architectural consistency.
  
  
  

Cross-Team Collaboration

• Work closely with data science teams to understand and support their requirements for machine learning experimentation and model deployment.
• Collaborate with AI engineering teams on architectural patterns that enable agentic AI workflows and advanced automation.
• Partner with data engineering teams to implement the architectural vision and ensure operational excellence.
• Engage with product and business stakeholders to translate business requirements into architectural decisions.
• Provide technical guidance and mentorship to implementation teams on architectural best practices.
  
  
  

Innovation and Optimization

• Stay current with the evolving Databricks platform and incorporate new capabilities into the architectural roadmap.
• Research and evaluate complementary technologies that enhance the core Databricks platform capabilities.
• Continuously optimize the data architecture for performance, cost efficiency, and scalability.
• Identify opportunities to leverage emerging patterns in data architecture, such as data mesh, data fabric, or domain-driven design.
• Develop proof-of-concepts to validate architectural approaches before full implementation.
  
  
  

What You Will Bring

• 8+ years of experience in data engineering, with at least 5 years focused on data architecture roles.
• 3+ years of hands-on experience with Databricks, including Delta Lake, Spark, and the broader Databricks ecosystem.
• Deep expertise in designing modern data platforms that support advanced analytics, machine learning, and AI use cases.
• Strong understanding of data modeling techniques for both structured and unstructured data in distributed computing environments.
• Experience designing architectures that support machine learning workflows, including feature engineering, model training, and deployment
• Proficiency with data orchestration tools and frameworks that integrate with Databricks.
• Hands-on experience with SQL, Python, and Scala for data processing and analysis.
• Knowledge of data governance, security, and compliance considerations in enterprise data architectures.
• Experience with cloud platforms (AWS, Azure, or GCP) and their native data services.
• Familiarity with modern software development practices, including version control, CI/CD, and infrastructure as code.
• Experience with designing architectures that support real-time and streaming data processing.
• Strong problem-solving skills and the ability to navigate complex technical and organizational challenges.
• Excellent communication skills with the ability to translate complex technical concepts to both technical and non-technical audiences.
• Bachelor’s degree in Computer Science, Information Systems, or related field; Master’s degree preferred.
• Professional certifications related to Databricks, cloud platforms, or data architecture are a plus.
  
  
  

If you are a person with a disability needing assistance with the application process please contact HR@resilinc.com.

Benefits

We offer comprehensive benefits that are specific to each country. Your talent acquisition contact can provide you with a FAQ list for your country. Everyone at Resilinc is eligible for healthcare coverage, participation in the employee stock option program, retirement benefits, paid time off and learning and development opportunities.

Resilinc is well-funded (read more about our recent investment from Vista Equity Partners), profitable, and shows no signs of slowing down. We run lean, work fast, and pivot quickly to accommodate our customers in order to keep supply chains moving. 

For more information visit our website:

Resilinc End-to-End Supply Chain Risk Management Solutions - Resilinc