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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 

 

        

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What You Should Know About Senior Data Architect - AI/ML Solutions / Databricks, Resilinc

Join the dynamic team at Resilinc as a Senior Data Architect specializing in AI/ML solutions and Databricks! Here at Resilinc, we believe in the transformative power of supply chains to make the world a better place, and we’re on a mission to provide cutting-edge supply chain visibility and analytics. In this role, you will take the helm of designing and implementing our enterprise data architecture, which is essential for our data strategy. You’ll work directly with the Director of Data Science to build scalable architectures that support our machine learning initiatives and innovative AI workflows. Your expertise in Databricks will be fundamental in creating the technical foundation for advanced analytics that drives our company forward. You’ll not only establish data governance practices to ensure our data remains secure but also create a roadmap that aligns with our broader data and AI strategy. If you're passionate about data architecture, eager to evolve through innovation, and ready to tackle complex challenges in a thrilling environment, this is the perfect opportunity for you. You will be working remotely with a group of motivated individuals dedicated to making lasting impacts. Resilinc is more than a workplace; it’s where your skills can spark major advancements in supply chain resilience. Join us to lead the charge in shaping the future of data architecture!

Frequently Asked Questions (FAQs) for Senior Data Architect - AI/ML Solutions / Databricks Role at Resilinc
What are the responsibilities of a Senior Data Architect at Resilinc?

The Senior Data Architect at Resilinc is responsible for designing and implementing a robust data architecture using Databricks. Key responsibilities include creating data modeling approaches, managing data governance policies, and overseeing architectural solutions that support advanced analytics and machine learning workflows.

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What qualifications are needed for the Senior Data Architect position at Resilinc?

To qualify for the Senior Data Architect role at Resilinc, candidates should have a minimum of 8 years of experience in data engineering, with at least 5 years in data architecture roles. Proficiency in Databricks, SQL, Python, and Scala, as well as knowledge of cloud platforms like AWS or Azure, are essential.

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How does the Senior Data Architect at Resilinc collaborate with other teams?

The Senior Data Architect collaborates closely with data science, AI engineering, and data engineering teams to understand requirements for machine learning, ensure successful implementation of architectural designs, and provide mentorship. This cross-team collaboration fosters an environment of innovation and operational excellence.

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What technical skills are essential for a Senior Data Architect at Resilinc?

Essential technical skills for a Senior Data Architect at Resilinc include expertise in modern data platforms, hands-on experience with Databricks, and knowledge of data orchestration tools. Additional skills in data modeling, real-time processing, and cloud services are also critical for success in this role.

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What opportunities for innovation exist for a Senior Data Architect at Resilinc?

At Resilinc, the Senior Data Architect will have the opportunity to stay current with evolving Databricks capabilities, optimize data architectures for efficiency and scalability, and explore emerging patterns like data mesh and domain-driven design, paving the way for cutting-edge advancements in data strategy.

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Common Interview Questions for Senior Data Architect - AI/ML Solutions / Databricks
How do you approach designing a data architecture using Databricks?

To design data architecture in Databricks, I would start by understanding the specific data requirements of the organization, then define data modeling techniques and establish efficient data ingestion workflows. I would also incorporate best practices for lakehouse architecture and ensure that security and governance measures are in place.

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Can you describe a challenging data problem you solved in a previous role?

In my last role, I faced performance issues with data ingestion from multiple sources. I implemented a new ETL strategy using Apache Spark on Databricks, which significantly improved the data processing rates and ensured easier scalability. This also allowed for smoother integration of machine learning workflows.

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What experience do you have with data governance and compliance in data architecture?

I have extensive experience in establishing data governance frameworks, including defining roles and responsibilities for data stewardship, creating data quality checks, and ensuring compliance with industry regulations. I always advocate for secure data practices within the architecture.

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How would you handle the integration of new AI services into an existing data platform?

To integrate new AI services, I would first evaluate the current architecture for compatibility. Then, I would design integration solutions that minimize disruption while ensuring performance and security, often employing APIs and microservices architecture to facilitate seamless connectivity.

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What strategies do you use to keep your data architecture scalable?

To keep data architecture scalable, I adopt modular design principles, ensure that we utilize cloud-native services, and regularly review performance metrics to identify bottlenecks. I also involve team feedback to anticipate future load and scalability needs.

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How do you keep abreast of the latest trends in data architecture?

I keep updated through attending industry conferences, participating in webinars, and engaging with professional networks focused on data architecture. Continuous learning is essential in this evolving field, and I often explore new technologies through hands-on projects.

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Describe your experience with real-time data processing.

I have implemented real-time data processing pipelines using Databricks' capabilities, such as structured streaming. By designing frameworks that efficiently manage data ingestion, transformation, and output within real-time scenarios, I’ve enabled timely analytics that drive business decisions.

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What methods do you use for data quality assurance?

For data quality assurance, I prioritize establishing validation checks at different stages of the data pipeline, incorporating automated testing frameworks for data integrity and consistency, and conducting regular audits to identify anomalies and areas for improvement.

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Discuss a time when teamwork led to a successful project delivery.

In a previous project, our data architecture team collaborated closely with data scientists and engineers to deliver a machine learning model within a tight deadline. By utilizing our individual strengths in architecture and automation, we facilitated an efficient deployment process that yielded significant insights.

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What is your approach to mentoring junior team members?

My mentoring approach focuses on hands-on guidance, encouraging questions, and fostering a growth mindset. I provide resources, share my experiences, and set up regular check-ins to ensure they feel supported in their technical development and career progression.

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. ....................................................... Our Purpose To STRENGTHEN the supply chains that power our lives. Our Mission To make global supply chains RESILIENT, SUSTAINABLE, FAIR and SECURE. .......................................

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March 20, 2025

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