Data Architect
Climb
Data Architect
Climb
AI consultancy delivering production-grade enterprise AI
Climb is a Data and AI consultancy that partners with enterprises to design, build, and operationalize modern data platforms and production AI systems. As a Databricks partner, we go deep on lakehouse architecture, machine learning, and applied AI, with a bias toward production over proof of concept. Our team brings deep technical expertise and a builder's mindset to every engagement, and we measure our work not just by what ships, but by the business impact it drives.
The Data Architect owns the technical architecture of the data platform on a client engagement. You translate business objectives into production-ready lakehouse architectures, defining the platform, governance, integration patterns, and implementation approach that delivery teams use to build scalable, secure, and AI-ready data systems.
This is a hands-on architecture role. You work closely with engineers throughout delivery, reviewing critical design decisions, validating architectural assumptions, and solving the most complex technical challenges. Your responsibility is to ensure the platform remains coherent as multiple data engineering workstreams come together into a reliable production system.
You partner with client technology leaders and Climb delivery teams to modernize enterprise data platforms, enabling trusted analytics, machine learning, and AI applications while balancing scalability, security, performance, and cost.
Own the end-to-end architecture of enterprise lakehouse platforms on Databricks, including workspace topology, governance, security, and data organization.
Define reference architectures, standards, and best practices that delivery teams build against.
Make and defend architectural decisions across data modeling, ingestion, orchestration, performance, scalability, security, governance, and cost.
Lead architecture for platform modernization and migration, including legacy warehouses, Hadoop ecosystems, and cloud-native data platforms.
Translate business objectives into technical roadmaps that balance delivery speed, operational excellence, and long-term platform evolution.
Serve as a trusted advisor to senior client architects and technology leaders.
Partner with the founders and delivery leads on pre-sales architecture, technical discovery, and solution design; help articulate value, ROI, and technical differentiation.
Establish architecture review standards and raise the technical bar across engagements.
Mentor senior and mid-level engineers; contribute reference implementations and accelerators back to the practice.
8+ years in data engineering, data architecture, or data platform roles, with significant time in customer-facing or advisory contexts.
Proven experience designing and delivering enterprise-scale lakehouse or data platform architectures.
Deep Databricks platform architecture expertise: Unity Catalog governance, multi-workspace design, security and identity, and Delta Lake at scale.
Strong command of distributed processing with Apache Spark and modern data modeling.
Experience across at least one major cloud (AWS, Azure, or GCP), with working knowledge of a second.
Demonstrated ability to communicate architecture decisions to both engineering teams and executive stakeholders.
Experience leading technical discovery, architecture workshops, or solution design during customer engagements.
Experience in regulated or data-intensive industries (financial services, healthcare, manufacturing).
Real-time and streaming architecture experience (Structured Streaming, Delta Live Tables, event-driven patterns).
Cost governance / FinOps experience for cloud data platforms.
Familiarity with the broader modern data stack and the Databricks partner ecosystem.
Note on certification: Existing Databricks certifications are a plus. Where not already held, Databricks certification (e.g., Data Engineer Associate/Professional) is expected to be obtained post-hire.
This role is designed for engineers who are ready to own complete workstreams today and are growing toward whole-system architecture and engagement leadership.
You naturally take ownership of complete workstreams rather than waiting for individual tasks.
You treat data quality, reliability, and performance as product features, not afterthoughts.
You enjoy solving ambiguous problems with practical engineering.
You leave every platform easier to operate than when you found it.
You'd rather ship something maintainable than demo something clever.
Ground floor, real backing. You are joining early, with founders who have built and exited firms like this before. You help write the playbook rather than inherit one.
Outcomes, not hours. We sell and deliver against business results. Advancement is tied to delivery performance and account impact, not utilization targets.
Senior team, no body-shop drag. Small pods of A-players, heavy internal AI leverage, and no bloated middle layers between you and the work.
IP that compounds. Every engagement feeds reusable accelerators, patterns, and points of view back into the practice.
Competitive base salary with performance-based bonuses
MacBook Pro and swag kit so you can do your best work
Comprehensive health, dental, and vision insurance
401(k) with company match
Generous holidays, flexible PTO, and remote-first work environment
Professional development budget including Databricks and cloud certifications
Spot bonuses for relevant certifications
Conference attendance and thought leadership opportunities
Collaborative, low-ego culture with direct access to leadership
Opportunity to shape a growing practice from the ground floor
Climb is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.
Climb provides AI consulting that moves enterprises from AI pilots to production-ready systems built on Databricks. Its fixed-scope Basecamp engagements move a data or AI priority from diagnostic to production within weeks, guided by a single end-to-end team and supported by the Climb AI Runtime. Unlike firms that bill by hour or use pyramid staffing, it uses outcome-aligned pricing and a dedicated team to accelerate delivery. The goal is to operationalize intelligence across core workflows and processes to deliver measurable business results, such as margin expansion and reduced cycle times.
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