Data & Analytics Engineer
Analytics
Bigquery
Business Intelligence
Cloud
Cloud Platform
Daasity
Data
Data Analysis
Data Analytics
Data Architecture
Data Build Tool
Data Engineer
Data Engineering
Data Integration
Data Management
Data Modeling
Data Pipeline
Data Pipelines
Data Platform
Data Processing
Data Visualization
Data Warehouse
Database
Databases
Dbt
ETL
Reporting and Analytics
SQL
Job Description
Benefits and culture
- Competitive salary plus bonus opportunities
- Unlimited PTO and sick time
- Company-paid medical, dental, and vision insurance
- Health and Wellness stipend of $100 per month
- Free Employee Assistance Program (EAP)
- Personal workspace stipend of $100 per month
- Annual merchandise allowance of $1,000
- 401(k) plan with 3% company match
The Data & Analytics Engineer role at True Classic is based onsite in Calabasas, CA and centers on owning the data platform infrastructure while connecting the data warehouse to AI, finance, and business stakeholders. The position emphasizes clean, well-structured pipelines, robust modeling, thorough testing, and clear documentation to enable reliable insights and automated workflows.
Role overview
As part of the team, you will design and operate the data foundation that supports cross-functional analytics and AI initiatives, ensuring data quality and accessibility for forecasting, planning, and decision making.
Responsibilities
- Design, build, and maintain modular dbt models with emphasis on testing, documentation, and code quality
- Contribute to completing open data model workstreams across inventory, media, and product domains
- Expand data source connections and broaden pipeline coverage for marketing and fulfillment systems
- Maintain and improve ETL and ELT workflows using Daasity and BigQuery
- Monitor and optimize cloud data infrastructure for cost efficiency and performance
- Deploy Omni dashboards on top of BigQuery to provide cross-functional visibility
- 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 queried by the AI team with clean, modeled BigQuery tables
- Use AI coding tools daily to write dbt models, debug pipelines, and accelerate development
- Collaborate with the AI team to ensure warehouse outputs support automation and real-time ops tools
- Identify opportunities where AI can automate data quality checks, anomaly detection, and pipeline monitoring
- 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
- Collaborate with merchandising, operations, and analytics stakeholders to translate business questions into reliable data models and visualizations
Requirements
- 4+ years of experience in data engineering or analytics engineering
- Strong understanding of data engineering best practices including pipeline design, data modeling, testing, and documentation
- Hands-on experience with dbt Cloud, Google BigQuery, and SaaS API pipeline development
- Solid SQL skills with 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)
- Comfort translating business questions to data models and visualizations for non-technical stakeholders
- Proficiency with AI coding tools; daily use expected
Technologies
- dbt Cloud
- Google BigQuery
- Daasity
- Looker
- GitHub
- Claude Code
- Cursor
- Copilot
- Python
- SQL
Location and work model
This position is on-site in Calabasas, CA, requiring five days per week in the office.
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