Data & AI Solution Architect

Job Description

Job Description

Job Title: Data & AI Solution Architect

Job Category: Software Development/ Engineering

Job Type: Contract

Location: Houston, Texas, United States

Data & AI Solution Architect

Position Description

Description:

This is a Solution Architect role with strong Data Architecture experience. It is not a Data Engineer, pure Data Architect or AI Architect role. The successful candidate must be capable of owning the end-to-end solution architecture & artefacts, while also personally developing the solution logical data architecture and guiding the physical data design.

We are seeking an experienced Solution Architect to deliver end-to-end architecture for projects within a major energy client, including solutions that enable data, analytics and AI use cases. The architect translates business goals and requirements into fit-for-purpose solution designs that align with business goals, technology direction, enterprise architecture principles and client standards.

The role requires independent delivery of high-quality architecture artefacts, including solution designs, Solution Logical Data Models and, where required, Physical Data Models. The architect evaluates solution options and trade-offs, considering value, affordability, do-ability and absorbability, identifies architecture risks and dependencies, and provides architecture direction and assurance through implementation.

This is primarily an individual contributor role. The architect will work independently on assigned project/solution deliverables, owning the architecture through delivery while working to the direction and priorities set by the Lead Architect.

Key Responsibilities & Deliverables

• Develop and maintain end-to-end solution and data architectures across applications, integrations, AI and data platforms to enable analytics, AI, GenAI and agent-based use cases where required by the business.

• Translate business and functional requirements into implementable architecture designs, evaluating solution options, trade-offs, risks and dependencies.

• Produce and maintain appropriate solution architecture artefacts, including:

o Solution context and architecture overview

o Solution/application component architecture and interaction views

o Data architecture and data-flow diagrams

o Interface, API and integration views

o Architecture decisions, risks, assumptions and dependencies

o Document and design to non-functional and security requirements

o Use existing business conceptual data models as inputs to develop project-specific Solution Logical Data Models (SLMs), defining the required entities, attributes, relationships and logical data structures; Develop or assure Physical Data Models (PDMs), where required, in collaboration with Data Engineers and development teams.

o Define appropriate patterns for exposing and consuming data through APIs, events, data pipelines, data products and enterprise data-platform capabilities.

o Where relevant, define how AI/GenAI capabilities integrate with the overall solution, data and technology architecture.

o Provide architecture direction for solutions using strategic platforms such as Microsoft Azure and Databricks, applying appropriate cloud, lakehouse, API, integration, batch/streaming and ETL/ELT patterns.

• Apply applicable client standards, reference architectures and strategic technology roadmaps, identifying and managing required step-outs.

• Work with business stakeholders, Data Architects, Data Engineers, application teams, security, platform teams and vendors to resolve design issues and drive architecture decisions. Produce architecture that is understandable to both technical delivery teams and business stakeholders.

• Provide architecture assurance throughout design and implementation to ensure the delivered solution conforms to the approved architecture and data models.

Required Experience & Skills

• Experience architecting data-intensive solutions that enable analytics, AI and GenAI use cases, including the data, integration, security and platform architecture required to operationalize those capabilities.

• Experience with structured solution optioning, architecture decision-making and architecture assurance.

• Strong practical experience in Data Architecture and Data Modeling - Solution Logical Data Models and Physical Data Models.

• Strong understanding of modern data architectures, integration patterns and platforms such as Azure and Databricks.

• Ability to balance business value, strategic alignment, delivery feasibility, technical quality and risk.

• Strong stakeholder management and communication skills, with the ability to explain complex architecture decisions clearly.

Preferred Experience & Skills

• Experience delivering architecture in Upstream, industrial, asset-intensive or operational environments is strongly preferred.

• Experience with integration of operational/OT, engineering, historian/time-series and enterprise IT data is an advantage.