Note: The job is a remote job and is open to candidates in USA. Wrapbook is an AI platform for production finance that helps finance teams manage payroll, spending, and accounting for film, television, and commercial productions. The Senior Analytics Engineer II will own and evolve the analytics layer, building reliable data foundations, governed metrics, self-serve analytics, and production monitoring while partnering with stakeholders and Engineering. The role also establishes standards for data quality, testing, documentation, and analytics operations so data can be used effectively by people and AI agents.
Responsibilities
- Lead the development of analytics products and self-serve tools so teams across Wrapbook can access trusted data and use it independently
- Own analytics products end to end, from defining success metrics and designing schemas through testing, production deployment, data quality, freshness SLAs, and incident resolution
- Build and maintain reliable ETL/ELT pipelines and canonical datasets that support analytical workflows across the company
- Build the governed data layer, including semantic models, canonical views, metric definitions, and data contracts. Maintain versioning and backward compatibility so downstream BI and AI consumers remain stable
- Structure models, definitions, and documentation so data is usable by people and by AI agents. Build internal tools that help teams ask data questions and trust the answers they receive
- Identify business questions, translate them into structured analytical problems, and develop data solutions that answer them
- Mentor the Analytics team by setting standards for testing, dbt CI/CD, monitoring, alerting, automation, runbooks, onboarding, and code review
- Partner with Engineering to understand source schemas, events, and system architecture. Provide input early so data entering the warehouse is reliable, stable, and easy to model
Skills
- 4+ years in data or analytics engineering. You've built and operated production pipelines end to end and owned issues when they broke
- Strong SQL and solid Python. Hands-on experience with ETL and orchestration tools (Airbyte, Fivetran, Dagster, dbt, Airflow, or similar), including multi-step workflows
- Experience with modern data warehouses (Snowflake, Databricks, or Redshift), including query and performance optimization
- Strong data modeling skills. You understand the business meaning behind the metrics, not just how the data moves
- A bias for action. You ship useful, iterative data models that deliver value without waiting for a perfect solution
- Experience building governed data layers (semantic models, canonical views, metric definitions, or data contracts)
- Experience writing data quality checks to validate data integrity (dbt tests, Great Expectations, Pydeequ, or similar)
- Experience with BI tools (Omni, Mode, Looker, Tableau, or similar). You've delivered reports and dashboards
- Experience setting standards for dbt CI/CD, monitoring, alerting, runbooks, and code review, and mentoring others on those practices
- A track record of evaluating and adopting new data and analytical tools when they solve a real problem or improve the stack
Benefits
- Unlimited Paid Time Off
- Work from anywhere in Canada and USA
- Health and Dental benefits
- Up to $1,500 USD/ $2,025 CAD towards IT set up for your home
- Up to 2% matching RRSP / 401K
- Learning and Development opportunities
- Up to $50 USD/ $67.50 CAD towards Internet/Cell phone service
Company Overview