Frame Data & Ai

DATABRICKS ARCHITECT

Job Requisition |Houston, TX | 3–5 Years of Experience

EXPERIENCE

3–5 years

CERTIFICATION

Databricks Data Engineer — required

WORK MODEL

Houston-based / client-facing

About Frame

Frame Data & AI is a Houston-based data and AI consulting firm serving energy, industrial, and other complex operating environments. We help clients modernize data foundations, build trusted data products, and apply analytics and AI to measurable business outcomes.

The Opportunity

We are seeking a hands-on Databricks Architect who can translate business and technical requirements into secure, scalable platform and solution designs and remain close enough to the work to guide implementation. This role combines architecture, data engineering, technical leadership, and client-facing consulting.

What You’ll Do

• Design Databricks lakehouse architectures across Azure, AWS, and/or GCP, with Azure experience strongly preferred.
• Lead solution design for batch, streaming, data integration, analytics, AI, and operational use cases.
• Define platform patterns for workspaces, networking, identity, security, environment separation, deployment, observability, and cost management.
• Design governed data products and Medallion architectures using Delta Lake and Unity Catalog.
• Guide engineering teams through implementation, conduct design and code reviews, and resolve complex technical issues.
• Build or oversee production pipelines using SQL, Python, Spark, Lakeflow, Workflows, and cloud-native services.
• Develop estimates, delivery approaches, architecture diagrams, technical roadmaps, and implementation plans.
• Facilitate client workshops and explain architecture decisions, tradeoffs, risks, and recommendations to technical and executive stakeholders.
• Support pre-sales discovery, solution shaping, demonstrations, and proposal development.
• Contribute reusable patterns, accelerators, and standards to Frame’s Databricks practice.

Required Qualifications

• 3–5 years of progressive experience in data engineering, cloud data platforms, or solution architecture, including at least 2 years of hands-on Databricks experience.
• Databricks Certified Data Engineer Associate or Databricks Certified Data Engineer Professional certification required at the time of hire.
• At least 1 year of hands-on experience with Databricks’ newer platform capabilities, including Lakeflow Declarative Pipelines, Lakeflow Connect, Unity Catalog, serverless compute and SQL warehouses, Mosaic AI (Model Serving, Vector Search, and Agent Framework), AI/BI Genie, Databricks Apps, and/or Lakebase.
• Strong hands-on proficiency with Python, SQL, Apache Spark, Delta Lake, and production data pipeline development.
• Demonstrated experience designing secure cloud architectures, including identity, networking, access controls, secrets, data governance, and environment strategy.
• Experience with CI/CD, infrastructure as code, automated testing, monitoring, and production support for Databricks solutions.
• Ability to create clear architecture diagrams and communicate technical decisions to both engineering teams and business stakeholders.
• Prior consulting or client-facing delivery experience, with the judgment to balance speed, quality, cost, and maintainability.

Preferred Qualifications

• Databricks Certified Data Engineer Professional, Machine Learning Professional, or Databricks Certified Generative AI Engineer Associate certification.
• Microsoft Azure architecture or data engineering certification.
• Experience with ERP, EAM, CMMS, IoT, historian, OT, or other industrial data sources.
• Experience in energy, industrial, manufacturing, utilities, or similarly operationally critical environments.
• Working knowledge of MLflow, feature engineering, retrieval-augmented generation, agentic AI, or AI application architecture.
• Experience estimating and leading small delivery teams through architecture, build, deployment, and transition to support.

What Success Looks Like

• Architectures are pragmatic, secure, cost-aware, and implementable by the delivery team.
• Clients understand the recommended approach and trust the technical decisions behind it.
• Engineering teams have clear patterns, guardrails, and hands-on leadership that improve delivery quality.
• Solutions move from design into production and create measurable operational or business value.

Why Frame

At Frame, you will work directly with experienced leaders and clients on meaningful Data & AI initiatives. You will have room to shape solutions, influence our Databricks practice, mentor engineers, and help build a consulting firm grounded in quality, trust, and real-world impact.