Senior Solution Architect role is responsible for assessing a complex marketing/campaign data process ecosystem. This will involve lead current-state discovery, facilitation of stakeholder working sessions, and providing a recommended architecture and delivery plan. Strong technical skills and knowledge of tools like SAS, cloud, and data science platforms are necessary for this 3-6 month contract position.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Position: Solutions Architect
Location: 100% remote
Duration: 3-6 month contract
Pay Rate: $60-$73/hr
Must Haves:
- 8–10+ years in solution architecture, business systems architecture, or technical program discovery
- Proven ability to enter ambiguous environments, untangle complexity, and drive structure quickly
- Strong experience with data/process architecture (end-to-end flow thinking, integration planning)
- Familiarity (working knowledge) with:
- SAS
- SQL
- Cloud concepts (data platforms, storage, compute; vendor-agnostic)
- Excellent stakeholder management and documentation skills (clear roadmaps, diagrams, requirements)
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Plusses:
- Banking or financial services experience
- Familiarity with campaign/marketing ecosystems:
- Unica Campaign / Unica Interact
- Salesforce Marketing Cloud
- Adobe Journey Optimizer
- Awareness of data science platforms (helpful):
- Dataiku
- SageMaker
- Light technical fluency in Python (not required to code, but helpful for credibility)
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Day to Day:
Our customer's Campaign & Data Enablement team is seeking a Solution Architect to quickly assess a complex, disconnected ecosystem of marketing/campaign data processes and tools. This person will drive current-state assessment, future-state design, and a recommended roadmap to consolidate, automate, and standardize workflows—enabling a Data Engineer to execute the build.
Responsibilities
- Lead current-state discovery across disconnected tools, data sources, and processes
- Facilitate working sessions with business and technical stakeholders to identify:
- pain points, manual steps, inefficiencies, and gaps
- target capabilities and future-state vision
- Produce a recommended architecture and delivery plan, including:
- data/process flows
- integration approach
- standardization and automation opportunities
- governance/process agreements and operating model suggestions
- Define implementation-ready requirements for the Data Engineer (handoff artifacts)
- Provide tool/technology guidance based on existing stack (SAS, cloud, data science tools, campaign platforms)
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