Senior Data & AI Solutions Architect

Senior Data & AI Solutions Architect

Data Architecture | Solutions Architecture | Azure | Databricks | AI

Downtown Houston, TX | 100% Onsite

$120–$150/hour | 1099 | 1-Year Contract-to-Hire

ElevationHR is seeking a Senior Data & AI Solutions Architect for a consulting engagement supporting a Data & AI services partner and its Houston-based Oil & Gas client.

This is a senior architecture position for someone who owns enterprise Data & AI solution design and remains technically close to implementation. You’ll define architecture, make technology decisions, guide engineering execution, and help move sophisticated Data, Cloud, and AI solutions from concept into production.

If your career has progressed into Data Architecture, Solutions Architecture, Cloud Architecture, Data & AI Architecture, AI Solutions Architecture, or Enterprise Architecture, this role is designed for you.

📍 At a Glance

• Location: Downtown Houston, TX
• Work Arrangement: 100% onsite
• Rate: $120–$150/hour
• Engagement: 1099
• Contract: 1-year contract-to-hire
• C2C: Not available
• Sponsorship: Must be authorized to work in the U.S. without current or future employer sponsorship
• Relocation: Local candidates preferred; candidates outside Houston must self-relocate
• Relocation Assistance: Not provided

Why This Role Matters

The challenge here isn't simply implementing another data pipeline or deploying another AI tool. You'll help determine how enterprise Data & AI solutions should be architected—how data is acquired, governed, processed and consumed; how Azure and Databricks fit into the broader architecture; how AI capabilities integrate with enterprise platforms; and how those designs remain secure, scalable, reliable and executable in production.

You'll operate as a technical design authority while staying close enough to Python, Databricks, Azure and modern AI technologies to challenge assumptions, evaluate tradeoffs, guide implementation and ensure the architecture works beyond the diagram.

What You'll Architect & Own

• Own end-to-end Data & AI solution architecture, from requirements and conceptual design through implementation and production.
• Define enterprise Data Architecture and Solutions Architecture, including architecture patterns, standards, roadmaps and technology direction.
• Architect scalable Microsoft Azure data platforms using services such as Azure Data Factory, Azure Synapse, ADLS and related Azure technologies.
• Design modern Databricks Lakehouse architectures leveraging Delta Lake, Unity Catalog, Databricks Workflows, Apache Spark and distributed processing.
• Architect enterprise data integration, ETL/ELT, batch and streaming architectures, data modeling and interoperability.
• Remain technically hands-on with Python, including the ability to develop, review and guide production implementation.
• Architect AI-enabled enterprise solutions incorporating Artificial Intelligence, Machine Learning and Generative AI.
• Design solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector search/vector databases, AI agents and intelligent automation.
• Incorporate MLOps/LLMOps, AI governance, evaluation, monitoring, security and production deployment into AI architecture.
• Establish architecture standards covering security, governance, lineage, data quality, scalability, reliability, interoperability and performance.
• Evaluate technical alternatives and make architecture decisions based on business requirements, engineering constraints and production considerations.
• Partner with senior stakeholders, architects, data and AI teams, and engineering leaders to guide solutions into production.

What You'll Bring

Must-Have

• 8+ years of relevant technology experience, including significant recent experience specifically in Data Architecture and/or Solutions Architecture.
• Recent responsibilities centered on architecture ownership and solution design, rather than primarily Data Engineering execution.
• Demonstrated experience working in architecture capacities such as Senior Data Architect, Data Architect, Solutions Architect, Cloud Solutions Architect, Data & AI Architect, AI Solutions Architect, Cloud Architect, or Enterprise Architect.
• Proven ownership of enterprise architecture decisions, solution design, technical standards and end-to-end delivery.
• Experience personally architecting complex enterprise data platforms and data solutions.
• Strong Microsoft Azure architecture experience.
• Strong hands-on Databricks and Lakehouse architecture experience, including technologies such as Delta Lake, Unity Catalog and Spark.
• Strong hands-on Python experience with the technical depth to develop, evaluate and review implementation.
• Deep understanding of Data Architecture, ETL/ELT, Data Integration, distributed processing, governance and enterprise data platforms.
• Demonstrated AI solution architecture experience—not simply exposure to AI initiatives.
• Experience designing AI-enabled solutions involving AI/ML, Generative AI, LLMs, RAG, AI agents, intelligent automation or related technologies.
• Understanding of MLOps/LLMOps, AI governance, security, monitoring and production AI deployment.
• Ability to own architecture while remaining technically engaged throughout implementation.
• Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or a closely related technical field.

Strongly Preferred

• Oil & Gas or Energy industry experience.
• Architecture experience within large, complex or regulated enterprise environments.
• Experience integrating Data + Cloud + AI architecture across multiple enterprise functions.
• Experience with technologies such as Snowflake, NVIDIA, Cognite, or other modern enterprise AI platforms.

Architecture vs. Engineering Fit

This distinction is important: this is an architecture role, not a Data Engineering role.

A strong Data Engineering foundation can be valuable, but the client needs someone whose career has progressed into dedicated architecture ownership.

If your recent responsibilities are primarily building pipelines, developing ETL processes, or implementing architectures designed by others, this position is unlikely to be the right match.

If you are now the person who defines the architecture, evaluates technology choices and tradeoffs, establishes standards, makes design decisions, and guides engineering teams through implementation, we want to hear from you.

What Will Make You Stand Out

Come prepared to discuss a solution where you personally:

Defined the architecture → selected the technology approach → incorporated Data & AI capabilities → remained technically engaged during implementation → guided the solution into production → delivered measurable value.

The strongest candidates can go beyond listing technologies. You should be able to explain:

• Which architecture decisions you personally owned
• Why you selected one approach over another
• What technical or business tradeoffs you evaluated
• How your architecture was implemented
• How you remained hands-on during delivery
• What measurable business or technical outcomes resulted

The Engagement

This is a 1-year, 1099 contract-to-hire engagement through ElevationHR supporting a Data & AI services partner and its Houston-based Oil & Gas client.

Rate: $120–$150/hour

Location: Downtown Houston, TX

Schedule: 100% onsite

C2C: Not available

Sponsorship: No current or future employer sponsorship

Relocation: No relocation assistance; non-local candidates must relocate at their own expense

Ready to Architect What's Next?

If you're an experienced Data or Solutions Architect who combines enterprise architecture ownership with hands-on expertise across Microsoft Azure, Databricks, Python and AI solutioning, apply through ElevationHR.

We're especially interested in architects who can demonstrate not just what they have worked with but what they personally designed, why they designed it that way, and how they helped bring it successfully into production.

Apply today to be considered!

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