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Senior Data Architect
Job Location:
Monthly Salary:
Posted:
23 May 2026 (30+ days ago)
Posted:
Application Deadline:
20 August 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Were seeking an experienced data architect who thrives at the intersection of business context and modern data engineering someone who can design end-to-end cloud data platforms for our top-tier omnichannel retail clients build the AI-ready data foundations these clients increasingly depend on and stay close enough to delivery to make sure those designs actually land.
This is a hybrid technical leadership role spanning both solution architecture during scoping and architectural oversight throughout delivery.
What are the responsibilities of a Senior Data Architect
Most architect roles are either scoping or delivery. This one is both. You scope the work and see it through. Roughly half your time goes to pre-sales by sitting with retail clients during discovery shaping what their cloud data platform should be and defending the design in front of their C-level. The other half goes to delivery staying close to the engineers building it reviewing their work and making sure the platform that ships is the one you designed.
The platforms themselves are modern omnichannel retail data stacks: cloud-native AI-ready and increasingly expected to power not just dashboards but machine learning (ML) models GenAI apps and AI agents. You will architect across the full stack but the part of the job thats distinctive isnt the stack; its the closeness to both the client conversation and the build.
The platforms themselves are modern omnichannel retail data stacks: cloud-native AI-ready and increasingly expected to power not just dashboards but machine learning (ML) models GenAI apps and AI agents. You will architect across the full stack but the part of the job thats distinctive isnt the stack; its the closeness to both the client conversation and the build.
Day to day you will:
- Lead architecture during discovery translating each clients business model KPIs and AI goals into a target-state design and implementation plan.
- Stay on as the design owner during build reviewing pipelines models and BI work from data and analytics engineers and unblocking the team when they hit hard calls.
- Architect AI-ready data foundations the semantic layers feature stores vector databases and embeddings pipelines that ML models GenAI apps and AI agents need to work reliably.
- Design end-to-end cloud platforms for retail clients: ingestion storage transformation modeling (dimensional Data Vault One Big Table or whatever fits) BI and CDP.
- Build engineering rigor in by default automated pipelines infrastructure-as-code CI/CD testing and observability so each platform gets cheaper and more reliable over time not the opposite.
- Co-sell with Business Developers Key Account Managers and Strategists shaping proposals defending estimates and presenting architectures to client stakeholders who range from skeptical CTOs to non-technical executives.
Platforms and tools youll work with:
- Cloud: AWS GCP Microsoft Fabric
- BI: Looker Studio Power BI Tableau
- CDP: Segment mParticle Bloomreach RudderStack Snowflake-native
- AI coding assistants: Claude Code Cursor Copilot in-warehouse LLM features
- Transformation & modeling: SQL dbt Python
What we expect from you
We hire for mindset and impact first. You should hold a clear technical opinion communicate well with both engineers and executives and stay practical about what each client needs.
Mindset
- Automation-first. You reach for infrastructure-as-code CI/CD testing and observability not runbooks and Slack pings. A good platform needs less babysitting over time not more.
- You know the trade-offs not just the brand names. You can say why BigQuery fits one client and Snowflake fits the next.
- You actually use AI coding assistants in your work generating SQL dbt and Python reviewing designs drafting docs not just opening Cursor once and closing it.
- You can defend an architecture to a skeptical CTO and a non-technical executive in the same room. You run workshops and challenge assumptions without putting people on the defensive.
Experience
- 5 years in data architecture engineering leadership or analytics engineering with at least three cloud platforms designed and shipped ideally in retail or e-commerce.
- Production experience across the stack below. You dont need every tool but you should be deep in at least one per category.
- A practical sense of what ML GenAI and AI agents need from a data platform feature stores embeddings vector databases RAG semantic layers governance lineage. We want someone who can learn fast across these not someone whos shipped all seven.
- Working knowledge of the BI and activation side dimensional modeling semantic layers CDPs identity resolution consent management and downstream activation into ad CRM and personalization tools.
scandiweb is an international company; therefore confident spoken and written English is essential.
What we offer
- Competitive starting salary relative to the market;
- Performance-based bonuses tied to successful project delivery and client outcomes;
- Exciting travel opportunities;
- Support for hardware upgrades;
- Core health insurance coverage and sports bonuses;
- A diverse multinational team of experts to learn from;
- Company-covered training and certification;
- Legendary online and onsite events to celebrate our success together.
Required Experience:
Senior IC
About Company
Scandiweb is a full-stack Magento agency with 10+ years of experience and the largest certified developer team in the world. Contact us today!
