Data Architect

At Lantern, our company culture stands as the bedrock of our success and a source of pride for our teams. We firmly believe that a culture founded on trust forms the basis for enduring relationships with clients, colleagues, and partners.

Within this culture, we nurture an environment of respect, inclusion, and belonging, fostering collaboration among inspired teams. We prioritize the well-being of our colleagues, the success of our clients, and our positive impact on society.
Embracing a growth mindset where curiosity thrives, we celebrate excellence and value individuals who inspire and mentor others, elevating the collective. Our driving force lies in personal and business growth. We go above and beyond to surprise and delight our clients, delivering tangible business value. In facing challenges, we make tough choices and solve complex problems to positively influence our clients, their customers, and the world at large.
As a Microsoft services partner, we hold ourselves to the highest standards of technical excellence. This commitment to quality is evident not only in our work but also in how we support and empower our employees. At Lantern, our culture mirrors our core values and unwavering dedication to realizing our purpose and vision, making it a dynamic and fulfilling workplace. Together, we transcend the ordinary and achieve extraordinary results.

Data Architect 

Lantern is seeking an experienced, client-facing Data Architect to lead enterprise data strategy, architecture, and delivery across Azure Databricks, Microsoft Fabric, Power BI, and Azure. 

You will advise business and technology leaders, modernize legacy platforms, and build secure, governed foundations for analytics, machine learning, generative AI, and intelligent applications. 

Key Responsibilities

• Lead client assessments, architecture workshops, modernization strategies, and delivery roadmaps. 
• Design secure, scalable lakehouse, warehouse, batch, streaming, and real-time solutions using Databricks, Fabric, Power BI, and Azure. 
• Define data integration, modeling, governance, quality, metadata, lineage, observability, security, and cost-management standards. 
• Establish semantic models, CI/CD, DevOps, DataOps, and deployment patterns for modern data platforms. 
• Guide delivery teams through architecture reviews, technical decisions, performance optimization, and troubleshooting. 
• Support proposals, estimates, demonstrations, reusable accelerators, and technical sales conversations. 
• Mentor engineers and consultants while strengthening Lantern’s Microsoft and Databricks capabilities.