Senior Data Architect - Snowflake & AI
Role details
Job location
Tech stack
Job description
As part of our Data & AI practice, you will work with major enterprise clients and global strategic accounts to help them transform and future-proof their data platforms - bringing both deep Snowflake mastery and strategic consulting expertise. You will act as lead architect and trusted advisor, guiding clients from data strategy through hands-on implementation, while championing AI-augmented engineering practices through Snowflake Cortex., * Lead data architecture engagements as the primary client-facing consultant, owning the relationship with technical and business stakeholders.
- Define and communicate data strategies aligned with client business objectives - from initial framing to executive presentation.
- Facilitate workshops, conduct discovery sessions, and co-create transformation roadmaps with client teams.
- Build and deliver structured consulting deliverables: architecture blueprints, AI-readiness assessments, governance playbooks, prompt libraries.
- Coach and upskill client data engineers on modern data practices, AI tooling, and Snowflake Cortex capabilities.
- Serve as the escalation point for complex architectural decisions, ensuring alignment across business, IT, and data teams.
Technical Architecture & Engineering
- Design and implement enterprise-grade Snowflake data architectures (data warehouse, data lakehouse, data mesh patterns).
- Lead the adoption of Snowflake Cortex for AI-native use cases: LLM-powered pipelines, intelligent data agents, and automated data workflows.
- Define data modeling standards (dimensional modeling, data vault, star schema) and govern their application across teams.
- Architect and oversee scalable ELT pipelines using dbt, Fivetran, and custom connectors.
- Drive data governance, access controls, security, and cost management best practices within Snowflake.
- Implement data quality frameworks and observability tooling (Monte Carlo, Datafold) with full lineage tracking.
- Establish CI/CD practices and DevOps standards for data platform deployments., * You think like a consultant first, an engineer second - you shape solutions, not just build them.
- You have delivered transformation programs leaving behind a playbook, a trained team, and measurable outcomes.
- You are energised by working across multiple client environments and bringing cross-industry patterns to each engagement.
- You can challenge a client's thinking constructively while maintaining trust and momentum.
- You have a genuine curiosity for AI, generative models, and the future of data engineering.
Requirements
As a Senior Data Architect - Snowflake & AI (all genders), you are passionate about experience innovation and eager to push the boundaries of what's possible. You bring +10 years of experience, a growth mindset and a drive to make a lasting impact., * A curious problem solver who challenges the status quo
- A collaborator who values teamwork and knowledge-sharing
- Excited by the intersection of technology, creativity and data
- Experienced in Agile methodologies and consulting (a plus), * +10 years of experience in data engineering or data architecture, with at least 5 years in a client-facing consulting or advisory role.
- Expert-level mastery of Snowflake: architecture, performance tuning, access controls, security, and Cortex AI features.
- Proven ability to lead complex data transformation programs from design through delivery.
- Strong experience with dbt, Fivetran/Stitch, Airflow, or equivalent orchestration tools.
- Deep knowledge of data modeling techniques and modern data stack best practices.
- Excellent communication and facilitation skills in French and English (C1) - able to present architecture choices to a CTO and explain them to a data engineer.
- Demonstrated ability to build trust with clients and drive organisational change., * Hands-on experience with Snowflake Cortex AI features: LLM Functions, Cortex Analyst, Cortex Agents.
- Knowledge of agentic AI frameworks, prompt engineering, and AI-assisted data engineering workflows.
- Experience with reverse ETL platforms (Hightouch, Census) and CDP architectures.
- Familiarity with streaming data platforms (Kafka, Kinesis, Pub/Sub) and real-time data patterns.
- Cloud platforms experience (GCP, AWS, Azure) and their native data services.
- Knowledge of data catalog and governance tools (Alation, Collibra, DataHub).
- SQL fluency and Python scripting proficiency.
Preferred certifications
- Snowflake SnowPro Core + Advanced/Architect (strongly preferred).
- dbt Analytics Engineering certification (a plus).
Benefits & conditions
Beyond a competitive compensation package, we offer:
- Flexibility, with remote and hybrid work options (country-dependent)
- Career advancement, with international mobility and professional development programs
- Learning and development, with access to cutting-edge tools, training and industry experts