Lead end-to-end cloud data platform design and delivery for omnichannel retail clients. Split time between pre-sales discovery and architectural oversight during build. Architect AI-ready data foundations (feature stores, embeddings, vector DBs), define ingestion, storage, transformation, modeling, BI and CDP integration, and enforce automation, IaC, CI/CD, testing, and observability. Co-sell and present architectures to technical and executive stakeholders.
We’re 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 that's distinctive isn't the stack; it's 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 that's distinctive isn't the stack; it's the closeness to both the client conversation and the build.
Day to day, you will:
- Lead architecture during discovery – translating each client's 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 you'll 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 don't 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 who's 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.
About
scandiweb is the leading digital experience partner for ambitious eCommerce brands. With over 20 years of expertise, we deliver enterprise-level solutions powered by AI, technological innovation, and the best talents globally.Our portfolio includes industry giants like Samsung, Läderach, Jaguar, BMW, Walmart, and Puma. Yet, our solutions go beyond platforms — we craft future-proof, high-performance digital ecosystems tailored to each client’s vision.With a focus on quality and innovation, we tailor our solutions to each brand’s unique goals — ensuring flexibility, scalability, and long-term success. Backed by an international team of top-tier professionals, we merge efficiency, strategy, and innovation to push eCommerce forward.At scandiweb, we work hard, innovate relentlessly, and celebrate success with purpose.
Similar Jobs
Big Data • Food • Hardware • Machine Learning • Retail • Automation • Manufacturing
Lead end-to-end recruitment for Experienced Hires across Greece and Central Europe. Partner with hiring managers to define requirements, source and assess candidates, manage candidate experience, build talent pools, and drive continuous improvement with TA leads and coordinators.
Top Skills:
ExcelMS OfficePhenomWorkday
Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical
Lead development and implementation of Medical Insights strategy and processes across Medical Affairs. Prioritize insights use cases, translate business needs into data/functional requirements, evaluate AI and analytics solutions, embed insights into medical decision-making, monitor impact, enable adoption of insights platforms, and collaborate cross-functionally to drive value and evidence generation.
Top Skills:
Advanced AnalyticsAIDataikuTableau
Artificial Intelligence • Machine Learning • Natural Language Processing • Software • Conversational AI
The Account Executive will build a sales pipeline in the German markets, work with cross-functional teams, and maintain stakeholder relationships to drive sales and manage accounts for Deepgram's voice AI platform.
Top Skills:
AISales TechnologySpeech-To-SpeechSpeech-To-TextText-To-SpeechVoice Ai
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
