Senior Data Architect

Stack

Responsibilities

• ▹Leading architecture during discovery: translating each client's business model, KPIs and AI goals into a target-state design and implementation plan
• ▹Staying on as design owner during build, reviewing pipelines, models and BI work from data and analytics engineers
• ▹Architecting AI-ready data foundations: semantic layers, feature stores, vector databases and embeddings pipelines
• ▹Designing end-to-end cloud platforms for retail clients: ingestion, storage, transformation, modeling, BI and CDP
• ▹Building engineering rigor in by default: automated pipelines, infrastructure-as-code, CI/CD, testing and observability
• ▹Co-selling with Business Developers, Key Account Managers and Strategists: shaping proposals, defending estimates, presenting architectures to client stakeholders

Requirements

• ▹Automation-first mindset: reaching for infrastructure-as-code, CI/CD, testing and observability
• ▹Knows the trade-offs, not just the brand names (e.g. why BigQuery fits one client and Snowflake the next)
• ▹Actively uses AI coding assistants (generating SQL, dbt and Python, reviewing designs, drafting docs)
• ▹Experience with: Cloud (AWS, GCP, Microsoft Fabric), BI (Looker Studio, Power BI, Tableau), CDP (Segment, mParticle, Bloomreach, RudderStack, Snowflake-native), Transformation & modeling (SQL, dbt, Python)
• ▹Clear technical opinions, strong communication with both engineers and executives

Soft skills