Principal Solution Architect

Acxiom • Conway, AR

1d • Remote

About The Position

We are seeking a highly experienced and hands-on Principal Solution Architect to join Acxiom’s Data & AI Consulting practice. This role is central to delivering enterprise-scale marketing transformation programs, with a focus on building modern marketing data platforms, enabling campaign execution, and structuring customer data for activation and measurement. You will lead the design and implementation of end-to-end marketing data ecosystems spanning data ingestion, modeling, identity-aware customer data design, campaign orchestration, and measurement. This includes establishing scalable data foundations (Snowflake, Databricks), defining how data supports real marketing workflows, and ensuring it is usable for both BI and AI-driven use cases. This is not a generic enterprise architecture role. Success requires a deep understanding of how marketing operates in practice, including campaign execution, audience targeting, suppression logic, and measurement frameworks, and the ability to translate that into practical, production-ready architectures. You will operate at the intersection of strategy and execution, working closely with cross-functional teams and client stakeholders to align business ambition with technical reality, guide implementation, and drive outcomes in complex, evolving environments. THIS POSITION IS NOT ELIGIBLE FOR ANY SORT OF SPONSORSHIP What You Will Do Engagement & Solution Leadership Serve as the solution architecture lead across the full platform lifecycle: discovery, design, and implementation Partner with strategy leads to translate business goals into technical architectures and executable roadmaps Lead client working sessions to define requirements around c ampaign workflows and operational dependencie s , customer data models, metadata structures, and identity-aware audience frameworks Ensure alignment between business use cases and technical feasibility, offering pragmatic alternatives when needed Marketing Data Architecture & Modeling Design and own end-to-end marketing data architecture, including: Data ingestion (Bronze), transformation (Silver), and consumption layers (Gold) Customer and campaign data models Metadata and taxonomy frameworks Define: Data grain, conformance logic, and key joins KPI logic and aggregation strategies Source-to-target mappings and field-level definitions Translate ambiguous business definitions into clear, scalable data structures and SQL logic Design customer data models that support identity stitching, audience persistence, and cross-channel activation Ensure data models are traceable, repeatable, and production-ready Platform & Integration Architecture Define solution blueprints across modern marketing ecosystems, including: Cloud data platforms (Snowflake, Databricks, BigQuery, Redshift) Cloud ecosystemts (AWS, Azure, GCP) CDPs and activation platforms (Adobe, Salesforce, Hightouch, LiveRamp) Clean rooms and CAPI integrations Design integrations across: CRM systems, campaign platforms, media data, and operational systems Ensure architecture aligns with: o Privacy, governance, and compliance requirements o Performance, scalability, and cost considerations Implementation & Delivery Leadership Lead architecture through build and deployment phases, ensuring: Designs translate into production-ready solutions Data pipelines and models are correctly implemented QA, validation, and reconciliation processes are in place Guide engineering teams and client stakeholders through: Technical decision-making Issue resolution and trade-offs Own delivery milestones and ensure successful translation of design into production-ready infrastructure. Navigate incomplete or evolving requirements by structuring delivery sequencing and minimizing rework Marketing Enablement & Measurement Ensure data and platform design supports: Campaign execution workflows (batch, triggered, omnichannel) Audience targeting, suppression, and personalization Measurement frameworks (attribution, incrementality, lift) Design data structures that enable: BI reporting AI/ML use cases (e.g., propensity, optimization, scenario planning, emerging AI-driven workflows) Ensure alignment between campaign design, data availability, and measurement outputs to avoid downstream rework Practice Leadership & Growth Contribute to practice development, including r eusable architecture patterns / frameworks , d elivery standards and best practices Support pre-sales by s haping solution approaches , e stimating effort and defining delivery models Mentor junior architects and engineers

Requirements

• 8+ years in solution architecture, data architecture, or platform implementation, with a strong focus on marketing and customer data
• Proven experience delivering end-to-end solutions (not just designing, but implementing)
• Deep expertise in: Marketing data ecosystems and campaign workflows
• Cloud data platforms (Snowflake, Databricks, etc.)
• Data modeling and transformation (SQL-heavy environments)
• Strong understanding of: Campaign execution, audience targeting, and suppression logic
• Marketing measurement frameworks (attribution, lift, etc.)
• Experience working with identity resolution and customer data frameworks (e.g., ID stitching, audience persistence, or partner integrations)
• Experience with: Multi-layer data architectures (e.g., Bronze / Silver / Gold)
• Source-to-target mappings, ERDs, data dictionaries, and KPI definitions
• Complex metric calculations (from a data perspective)
• Ability to: Translate business ambiguity into structured technical solutions
• Communicate architecture clearly to both technical and non-technical stakeholders
• Strong familiarity with: Martech ecosystem (CDPs, CRM, campaign platforms)
• Data governance and privacy considerations

Nice To Haves

• Experience in consulting or professional services
• Experience in regulated industries (financial services, healthcare, automotive)
• Familiarity with: Clean rooms and data collaboration environments
• Advanced measurement (incrementality testing, MMM inputs)
• AI/ML enablement within marketing use cases

Responsibilities

• Serve as the solution architecture lead across the full platform lifecycle: discovery, design, and implementation
• Partner with strategy leads to translate business goals into technical architectures and executable roadmaps
• Lead client working sessions to define requirements around c ampaign workflows and operational dependencie s , customer data models, metadata structures, and identity-aware audience frameworks
• Ensure alignment between business use cases and technical feasibility, offering pragmatic alternatives when needed
• Design and own end-to-end marketing data architecture, including: Data ingestion (Bronze), transformation (Silver), and consumption layers (Gold)
• Customer and campaign data models
• Metadata and taxonomy frameworks
• Define: Data grain, conformance logic, and key joins
• KPI logic and aggregation strategies
• Source-to-target mappings and field-level definitions
• Translate ambiguous business definitions into clear, scalable data structures and SQL logic
• Design customer data models that support identity stitching, audience persistence, and cross-channel activation
• Ensure data models are traceable, repeatable, and production-ready
• Define solution blueprints across modern marketing ecosystems, including: Cloud data platforms (Snowflake, Databricks, BigQuery, Redshift)
• Cloud ecosystemts (AWS, Azure, GCP)
• CDPs and activation platforms (Adobe, Salesforce, Hightouch, LiveRamp)
• Clean rooms and CAPI integrations
• Design integrations across: CRM systems, campaign platforms, media data, and operational systems
• Ensure architecture aligns with: o Privacy, governance, and compliance requirements o Performance, scalability, and cost considerations
• Lead architecture through build and deployment phases, ensuring: Designs translate into production-ready solutions
• Data pipelines and models are correctly implemented
• QA, validation, and reconciliation processes are in place
• Guide engineering teams and client stakeholders through: Technical decision-making
• Issue resolution and trade-offs
• Own delivery milestones and ensure successful translation of design into production-ready infrastructure.
• Navigate incomplete or evolving requirements by structuring delivery sequencing and minimizing rework
• Ensure data and platform design supports: Campaign execution workflows (batch, triggered, omnichannel)
• Audience targeting, suppression, and personalization
• Measurement frameworks (attribution, incrementality, lift)
• Design data structures that enable: BI reporting
• AI/ML use cases (e.g., propensity, optimization, scenario planning, emerging AI-driven workflows)
• Ensure alignment between campaign design, data availability, and measurement outputs to avoid downstream rework
• Contribute to practice development, including r eusable architecture patterns / frameworks , d elivery standards and best practices
• Support pre-sales by s haping solution approaches , e stimating effort and defining delivery models
• Mentor junior architects and engineers

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed
• Number of Employees: 501-1,000 employees