Solution Architect
- Houston, TX, United States
Applications open in a new tab.
Job details
- Experience
- 10+ years of experience in technology, with at least 5 years in a Solution, Enterprise, Data or Integration Architect role.
- Posting language
- English
- Posted
Original job description
Agencies: We only accept applications through this LinkedIn posting or from staffing partners under a signed agreement with Indigo Beam. Unsolicited candidate emails to our team will not be reviewed, create no fee obligation, and will result in the sender’s domain being blocked.
Location: Houston, TX
Joining: Immediate
Work Authorization: Visa independent candidates
Engagement: Contract: approx. 8 weeks (296 hours), 40h/week
Solution Architect | Connected Customer, Marketing, Data, Analytics & AI
This Architect role sits within our client’s Architecture team, supporting its Mobility and Retail business in the Americas. The focus is on Connected Customer, Marketing, Data, Analytics and AI, as well as Solution and Integration Architecture.
The role helps shape how the client creates connected, insight-driven customer experiences across mobility, retail, loyalty, digital channels and marketing. It translates business strategies and customer needs into scalable solution architectures aligned with enterprise standards, design principles, data policies and technology strategy.
The role reports to the Lead Architect and works across business, product, data, marketing, digital, country and technology teams to ensure that customer and marketing capabilities are designed as connected, reusable and insight-driven services rather than isolated solutions.
Key Responsibilities
- Translate customer, business, marketing and operational requirements into solution architectures, architecture models, documentation and decision records for products, projects and platforms.
- Shape architectures that support connected customer journeys across digital channels, retail sites, loyalty, CRM, marketing activation, personalisation, customer service and partner ecosystems.
- Define how customer identity, consent, preferences, behavioural data, transaction data and campaign interactions are connected and used responsibly across the customer ecosystem.
- Design reusable customer and marketing capabilities, including customer profiles, segmentation, loyalty, offers, campaign orchestration, personalisation, customer analytics and measurement.
- Architect data, analytics and AI solutions, including trusted data products, semantic models, customer 360 capabilities, advanced analytics, machine learning and generative AI.
- Ensure customer and marketing solutions support consistent experiences across countries while allowing for local propositions, regulatory requirements, partner models and channel needs.
- Assure standards conformance, security, privacy, consent, supportability, value and affordability, particularly for solutions involving customer data and marketing activation.
- Design solutions using Azure, the client’s enterprise data platforms, Databricks and cloud-native data and integration technologies.
- Apply data governance and information management, including metadata, lineage, quality, discoverability, retention, consent and responsible use of customer data.
- Define integration patterns between customer, loyalty, marketing, digital, retail, payment, CRM, data and partner platforms.
- Assess opportunities to reuse the client’s existing platforms, enterprise services, data products and integration patterns before introducing new technology or capabilities.
- Use AI-enabled architecture practices and automation to accelerate repeatable deliverables, including solution options, architecture models, decision records, data mappings, interface specifications, requirements traceability, test scenarios and governance evidence.
- Identify opportunities to automate architecture and delivery activities using generative AI, APIs, scripts, workflow tools and reusable templates, improving consistency, quality and time to value.
- Apply human review and appropriate governance when using AI to analyse business information or generate architecture artefacts, including consideration of security, privacy, confidentiality, traceability and accuracy.
- Help teams adopt practical AI-assisted ways of working through reusable prompts, patterns, templates and automation approaches.
- Work across the complex country, business partner and application landscape, identifying dependencies, capability gaps, integration constraints and opportunities to simplify the customer and marketing ecosystem.
- Collaborate with Customer, Marketing, Loyalty, Digital, Data, Analytics, Product, Architecture, Engineering, Security, Privacy, Country, Application Hosting, Solution Architecture and Identity & Access Management teams to align on priorities, resolve design decisions and ensure solutions move smoothly from concept to delivery and operation.
Requirements
- 10+ years of experience in technology, with at least 5 years in a Solution, Enterprise, Data or Integration Architect role.
- Proven experience designing customer-facing architectures across CRM, loyalty, marketing automation, personalisation, digital channels or retail, ideally in a multi-country or B2C environment.
- Strong knowledge of customer data concepts, including Customer 360, customer identity resolution, consent and preference management, segmentation and Customer Data Platforms (CDP).
- Hands-on experience with marketing technology platforms such as Salesforce (Marketing Cloud, Data Cloud, Service Cloud), Adobe Experience Platform, Braze, Segment or similar.
- Solid experience in data, analytics and AI architecture, including data products, semantic models, data lakehouse patterns, machine learning and generative AI use cases.
- Hands-on experience with Microsoft Azure and Databricks, including cloud-native data, integration and analytics services.
- Strong integration architecture background, including APIs, event-driven architecture, messaging, ETL/ELT and integration platforms (e.g. Azure Integration Services, MuleSoft, Kafka or similar).
- Working knowledge of data governance and information management, including metadata, lineage, data quality, master data, retention and responsible use of customer data.
- Solid understanding of privacy and data protection regulations (e.g. GDPR, CCPA, LGPD) and how they shape the design of customer and marketing solutions.
- Experience with security and identity concepts, including IAM, CIAM, authentication, authorisation and data protection controls.
- Practical experience using generative AI and automation in architecture or delivery work, such as prompts, templates, scripts or workflow tools to speed up repeatable deliverables.
- Ability to produce clear architecture artefacts, including solution designs, architecture models, decision records, interface specifications and data mappings.
- Familiarity with architecture frameworks and methods such as TOGAF, ArchiMate, C4 or similar.
- Proven ability to work in complex, matrixed organisations, influencing senior stakeholders across business, technology, country and partner teams.
- Strong communication skills, with the ability to explain technical concepts to non-technical audiences and translate business strategy into technical direction.
- Fluent English, written and spoken.