Databricks Architect
Req number:
R8699
Employment type:
Full time
Worksite flexibility:
Remote
Who we are
CAI is a global services firm with over 9,000 associates worldwide and a yearly revenue of $1.3 billion+. We have over 40 years of excellence in uniting talent and technology to power the possible for our clients, colleagues, and communities. As a privately held company, we have the freedom and focus to do what is right—whatever it takes. Our tailor-made solutions create lasting results across the public and commercial sectors, and we are trailblazers in bringing neurodiversity to the enterprise.
Job Summary
We are looking for a motivated Databricks Architect ready to take us to the next level! If you have lead the design, implementation, governance, and optimization of enterprise-scale data and AI platforms on Databricks and are looking for your next career move, apply now.
Job Description
We are looking for a Databricks Architect to lead the design, implementation, governance, and optimization of enterprise-scale data and AI platforms on Databricks. This position will be full-time and remote.
What You'll Do
Define and own the enterprise Databricks architecture strategy, ensuring scalability, security, reliability, and alignment with business and AI objectives
Design modern data platforms leveraging Databricks Lakehouse, Delta Lake, Unity Catalog, and AWS services
Lead the architecture and modernization of data warehouses, data lakes, and analytical platforms into scalable Lakehouse architectures
Establish enterprise standards, frameworks, and best practices for data ingestion, transformation, orchestration, governance, and consumption
Design and implement secure, high-performance batch and real-time data processing solutions
Develop reference architectures for data engineering, advanced analytics, machine learning, and generative AI workloads
Define data governance, lineage, metadata management, security, and compliance standards across the data platform
Architect scalable and reusable data models that support reporting, analytics, operational intelligence, and AI use cases
Guide implementation teams on platform setup, workspace design, networking, access controls, monitoring, and operational readiness
Drive platform optimization initiatives related to compute utilization, workload management, storage performance, and cost efficiency
Lead architectural reviews and provide oversight for critical data and AI initiatives
Collaborate with business stakeholders, product owners, data engineers, ML engineers, and cloud teams to translate requirements into technical solutions
Establish observability frameworks for monitoring platform health, performance, data quality, and usage patterns
Evaluate emerging Databricks capabilities and recommend adoption strategies that enhance business value
Develop migration strategies and execution roadmaps for legacy data platforms transitioning to Databricks
Define disaster recovery, business continuity, backup, and resilience requirements for enterprise data platforms
Drive architecture governance through design reviews, standards enforcement, and continuous improvement initiatives
Mentor engineering teams and provide technical leadership on complex architecture decisions
Deliver executive-level architecture documentation, roadmaps, solution blueprints, and technology recommendations
Hands-on experience with both AWS and Azure cloud platforms, including architecture design, security, networking, storage, governance, and data services
Strong understanding of multi-cloud data platform strategies and the ability to architect solutions across AWS and Azure environments
Experience integrating Databricks with AWS and Azure native services to support enterprise analytics, data engineering, and AI use cases
What You'll Need
Required:
Bachelor's degree or higher in Computer Science, Information Technology, Engineering, Data Science, or a related field
10+ years of experience in data engineering, data…