Senior Customer Architect
New
North America and beyond, with strong communities in New York, San Francisco, and TorontoFull-TimeSenior
Salary180000 - 200000 CAD per year
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Job Details
- Experience
- 3-5 years
- Required Skills
- AWSPythonSQLArtificial IntelligenceETLGCPSnowflakeAzureRESTful APIsBigQueryRedshiftDatabricks
Requirements
- 3-5 years in a client-facing technical role: solutions architecture, implementation engineering, technical customer success, or marketing analytics
- Strong proficiency in SQL
- Hands-on experience querying cloud data warehouses (BigQuery, Snowflake, Redshift, or Databricks)
- Demonstrated ability to lead complex, multi-stakeholder technical projects from kickoff through delivery
- Experience with cloud infrastructure (GCP, AWS, or Azure)
- Experience with data pipeline concepts (ETL/reverse ETL, event streaming, data modeling)
- Excellent communication skills
- Hands-on experience working with LLMs and AI tools (e.g., Claude, GPT-4, Gemini) for practical use cases
- Ability to design and build prompt-based workflows or LLM-powered automations using APIs, Python, or no-code tools (e.g., n8n, Zapier)
- Experience identifying opportunities for operational efficiency and leveraging AI tools
- Comfort evaluating AI outputs for accuracy, hallucination risk, and fitness for customer-facing use
Responsibilities
- Own a portfolio of strategic accounts
- Lead complex technical implementations
- Use AI to help automate workflows and drive value faster
- Lead end-to-end onboarding projects for enterprise customers
- Own the technical implementation of GrowthLoop across cloud data warehouses, destination integrations, and data modeling
- Build and maintain project artifacts: project GANTTs, kickoff decks, use case trackers, data workshop materials
- Own a book of business as the primary technical point of contact post-onboarding
- Deliver executive-facing QBRs and EBRs articulating business impact and roadmap
- Identify expansion opportunities and troubleshoot complex data, integration, and pipeline issues
- Enable agentic workflows for audience ideation, campaign optimization, and performance analysis
- Stay current on AI/ML developments in martech and proactively bring new capabilities to customers
- Build AI-powered automations and internal tools for the CA team
- Contribute to LLM-powered agents for customer research, escalation management, and onboarding acceleration
- Document and share repeatable playbooks
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