Databricks Field CTO

Blend360; United States; On-site; USD 180,000 - 280,000; Full time

Job summary

Blend360 is seeking a Databricks Field CTO to accelerate our Databricks business across North America. You will blend executive advisory, technical pre-sales, and architecture leadership to shape engagements and deliver production-grade data and AI solutions.

You will guide enterprise-scale architectures, collaborate with client partners, delivery teams, and Databricks specialists, and set standards, accelerators, and reusable patterns to drive impact at scale.

Qualifications

• 15+ years of experience in data or cloud architecture.
• Deep Databricks expertise with production-scale solutions.
• Strong knowledge of Spark, Delta Lake, Unity Catalog, and Databricks SQL.
• Experience with AI/ML pipelines and governance.
• Proven client-facing advisory and pre-sales leadership.

Responsibilities

• Shape opportunities with Client Partners and BD to craft proposals and workshops.
• Translate priorities into architectures, roadmaps, and business outcomes.
• Design architectures across lakehouse modernization, analytics, ML, and AI.
• Lead critical architecture decisions ensuring security, reliability, and cost control.
• Mentor teams and develop reusable patterns and accelerators.

Skills

Databricks

Cloud architecture

Pre-sales

Leadership

Python

SQL

Tools

Spark

Delta Lake

Unity Catalog

Databricks SQL

MLflow

Job description

As Blend's Databricks Field CTO, you will help grow our Databricks business across North America, combining executive advisory, technical pre-sales, and architecture leadership. You will work with Blend Client Partners, Business Development leaders, and Databricks field teams to identify opportunities, shape engagements, and help clients translate their data and AI ambitions into production solutions.

You will serve as a senior technical authority for Databricks engagements, guiding platform decisions and helping delivery teams navigate complex architecture, integration, governance, and operational challenges. Internally, you will work with architects, data engineers, and AI practitioners globally to establish standards, strengthen technical capabilities, and develop reusable solutions and accelerators.

You bring deep technical credibility, commercial judgment, and enthusiasm for data and AI. You are equally comfortable whiteboarding with engineers, leading a client executive discussion, and working alongside delivery teams to resolve a difficult technical problem.

Responsibilities

Platform Architecture and Technical Pre-Sales

• Partner with Blend's Client Partners and Business Development leaders to shape Databricks opportunities, supporting discovery, proposals, architecture workshops, demonstrations, and hands-on labs.
• Translate client priorities into solution architectures, delivery roadmaps, effort estimates, and clearly defined business outcomes.
• Design architectures spanning lakehouse modernization, batch and streaming data engineering, analytics, machine learning, and generative and agentic AI.
• Establish approaches for governance, security, data quality, interoperability, performance, and cost management.
• Work directly with Databricks account teams, Solutions Architects, and specialists to develop joint solutions and support co-sell opportunities.

Technical Leadership and Delivery

• Guide critical architecture decisions and validate proposed solutions against enterprise scale, reliability, security, and operational requirements.
• Help teams resolve complex challenges across data pipelines, cloud infrastructure, integrations, governance, and production AI systems.
• Maintain continuity from pre-sales through delivery, ensuring that scope, assumptions, architecture decisions, and success criteria are understood.
• Provide hands-on support for strategic proofs of concept, reference implementations, architecture reviews, and delivery escalations.
• Help clients move from experimentation to production with appropriate evaluation, monitoring, deployment, and support practices.

Practice Development and Databricks Community

• Work across Blend's global teams to establish architecture standards, reusable patterns, accelerators, and delivery guidance.
• Mentor architects and engineers, support technical hiring, and help build a collaborative Databricks community within Blend.
• Coordinate with Databricks counterparts on technical enablement, certifications, and emerging platform capabilities.
• Turn successful engagements into repeatable offerings, demonstrations, case studies, and thought leadership.

Executive Engagement and Go-to-Market Alignment

• Advise client CTOs, CIOs, CDOs, and business leaders on data and AI strategy, platform modernization, and adoption priorities.
• Explain architectural tradeoffs in terms of business value, implementation effort, cost, risk, and time to value.
• Partner with Blend's practice and alliance leaders to align technical investments with client demand and joint Databricks opportunities.
• Represent Blend in client workshops, partner discussions, and relevant industry events.

Required

• 15+ years of experience in data, platform, or cloud architecture, including at least five years focused on Databricks, modern data platforms, or related solution engineering and technical pre-sales.
• Deep hands-on Databricks experience, with a track record of designing and delivering enterprise production solutions.
• Strong expertise in Apache Spark, Delta Lake, Unity Catalog, Databricks SQL, and batch and streaming architectures, with practical Python and SQL skills.
• Experience with Databricks data engineering and orchestration capabilities, including Lakeflow, and the design of reliable, governed data pipelines.
• Hands-on experience designing and delivering AI and agentic solutions on Databricks, using capabilities such as Agent Bricks, Mosaic AI Model Serving, Vector Search, and Genie for document retrieval, conversational analytics, and business workflow automation.
• Experience connecting agents to enterprise data, tools, and APIs through MCP and Unity Catalog functions, with appropriate identity, permissions, and governance.
• Experience taking AI solutions into production, including MLflow evaluation and tracing, deployment through Databricks Apps or serving endpoints, and security, monitoring, and cost controls through Unity Catalog and Unity Gateway.
• Strong cloud architecture experience on A