True Classic is hiring a
Data & Analytics Engineer to partner in owning our data platform infrastructure and to serve as a key builder connecting our data warehouse to our AI, finance, and business stakeholder teams. This role will support core analytics engineering functions, ensuring clean, well-structured, and reliable data pipelines built to best practice standards.
This role is ideal for someone who is hands-on and technically rigorous, with a strong command of data engineering best practices - including pipeline design, data modeling, testing, and documentation - and can contribute meaningfully to a mid-build platform in a fast-paced, evolving environment.
Areas of AccountabilityExtend & Maintain the Data Platform- Build and maintain dbt models following best practices for modularity, testing, documentation, and code quality
- Contribute to completion of open data model workstreams across inventory, media, and product functions
- Expand data source connectivity and pipeline coverage across marketing and fulfillment systems
- Maintain and improve ETL/ELT workflows via Daasity and BigQuery
- Help monitor and optimize cloud data infrastructure for cost and performance
Bridge Data to the Business- Deploy and maintain Omni dashboards on top of BigQuery for cross-functional stakeholders
- Support business KPI tracking by structuring financial data for forecasting, cost modeling, and channel-level P&L
- Contribute to predictive models for demand forecasting, inventory planning, and revenue projections
- Build and maintain the serving layer that the AI team queries - clean, modeled BigQuery tables in place of direct API calls
AI-Augmented Development- Use AI coding tools (Claude Code, Cursor, Copilot) daily to write dbt models, debug pipelines, and accelerate development
- Collaborate with the AI team to ensure the warehouse serves their applications with clean inputs for automation, ML models, and real-time ops tools
- Identify opportunities where AI can automate data quality checks, anomaly detection, and pipeline monitoring
Cross Functional Collaboration- Work with finance to ensure financial data structures support forecasting and P&L reporting needs
- Partner with the AI team to ensure warehouse outputs support downstream automation and machine learning applications
- Work alongside merchandising, operations, and analytics stakeholders to translate business questions into reliable data models and visualizations
Qualifications- 4+ years of experience in data engineering or analytics engineering
- Strong understanding of data engineering best practices: pipeline design, data modeling, testing, and documentation
- Hands-on experience with dbt Cloud, Google BigQuery, and SaaS API pipeline development
- Strong SQL skills including joins, window functions, and CTEs
- Python proficiency for pipeline scripting, API integrations, and light modeling
- Familiarity with statistical modeling and predictive analytics (regression, time series)
- Comfortable working with non-technical stakeholders to translate business questions into data models and visualizations
- Proficiency with AI coding tools - daily use expected
Preferred Qualifications- NetSuite or ERP experience
- Daasity, Shopify/Amazon data
- Marketing attribution platforms (Meta CAPI, Google Ads, Triple Whale),
- Omni/Looker, GitHub-based workflows
Workplace ArrangementThis role is on-site (5x week in office) based in Calabasas, CA.
Compensation and BenefitsCompensation- Competitive Salary + bonus
Time Off- Unlimited PTO and sick time
Health & Wellness- Company-paid medical, dental, and vision insurance
- $100/month Health & Wellness stipend
- Free Employee Assistance Program (EAP)
Work & Growth Support- $100/month Personal Workspace/Office stipend
Perks- $1,000/year True Classic merchandise allowance
- 401(k) plan with 3% company match
