Databricks Field CTO

Blend360•Columbia, MD

1d•$260,000 - $275,000

About The Position

As Blend’s Databricks Field CTO, you will help grow the company’s Databricks business across North America through 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 turn 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 address complex architecture, integration, governance, and operational challenges. You will also work with Blend’s global architects, data engineers, and AI practitioners to establish standards, strengthen technical capabilities, and develop reusable solutions and accelerators. The role calls for deep technical credibility, commercial judgment, and enthusiasm for data and AI. You should be comfortable working with engineers, leading executive client discussions, and collaborating with delivery teams to solve technical problems.

Requirements

At least 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 and 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 designing 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 AWS, Microsoft Azure, or Google Cloud, including identity, networking, storage, security, and deployment automation.
Experience leading data platform migrations or modernization programs, including architecture, workload transition, performance, and cost considerations.
Demonstrated success working alongside sales teams and engaging directly with senior client executives.
Experience collaborating with Databricks field teams on joint opportunities and technical solution development.
Background in consulting, professional services, or an embedded technology partner role.

Nice To Haves

Relevant Databricks professional certifications, including data engineering, machine learning, or generative AI.
Experience with enterprise governance, data sharing, federation, and open table formats.
Familiarity with Databricks partner programs, Marketplace, and developing repeatable industry solutions.
Experience establishing technical communities, mentoring senior practitioners, and developing reusable delivery assets.

Responsibilities

Partner with Client Partners and Business Development leaders to shape Databricks opportunities through discovery, proposals, architecture workshops, demonstrations, and hands-on labs.
Translate client priorities into solution architectures, delivery roadmaps, effort estimates, and defined business outcomes.
Design architectures for lakehouse modernization, batch and streaming data engineering, analytics, machine learning, and generative and agentic AI.
Establish approaches to governance, security, data quality, interoperability, performance, and cost management.
Work with Databricks account teams, Solutions Architects, and specialists to develop joint solutions and support co-sell opportunities.
Guide critical architecture decisions and validate proposed solutions against enterprise-scale, reliability, security, and operational requirements.
Help teams resolve complex challenges involving data pipelines, cloud infrastructure, integrations, governance, and production AI systems.
Maintain continuity from pre-sales through delivery, ensuring 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 AI solutions from experimentation to production with suitable evaluation, monitoring, deployment, and support practices.
Establish architecture standards, reusable patterns, accelerators, and delivery guidance across Blend’s global teams.
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.
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 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.