Data Engineer (Contract)
Indexed description
The ideal candidate has deep expertise in BigQuery, dbt, and Looker, with hands-on experience modeling complex eCommerce data from platforms such as Shopify, Klaviyo, subscription systems (e.g., Loop), and 3PL providers
Key Responsibilities
• Design, build, and maintain scalable data pipelines using BigQuery and dbt
• Architect and optimize warehouse-first data models to support analytics, marketing, and operational reporting
• Develop and maintain Looker dashboards and semantic layers
• Integrate and transform data from Shopify, Klaviyo, Loop (subscriptions/returns) and 3PL systems (e.g., ShipHero, ShipBob, etc.)
• Build automated workflows for data ingestion, validation, and monitoring
• Implement best practices for data quality, governance, and documentation
• Leverage AI tools (LLMs, automation frameworks) to:
- Accelerate data transformation workflows
- Refactor and optimize SQL/dbt models
- Automate anomaly detection and QA processes
• Troubleshoot data discrepancies and provide root-cause analysis
• Recommend architectural improvements to improve performance, reliability, and scalability
Service Level Agreements (SLAs)
- Response Time: Acknowledge requests within 24 hours
- Critical Issues (P0): Immediate response and active resolution
- Standard Requests: Timeline provided within 72 hours
- Billing Model: Time & materials based on agreed scope and hours worked
• Advanced experience with BigQuery, Dbt, SQL performance optimization
• Experience building and maintaining Looker dashboards and data models
• Strong understanding of:
- eCommerce metrics (AOV, LTV, churn, CAC, retention)
- Marketing attribution
- Subscription data structures
• Experience implementing data quality checks and validation pipelines
• Strong written and verbal communication skills
• Ability to work independently with minimal oversight
Preferred Qualifications
- Experience working with distributed or agency environments
- Experience supporting DTC brands
- Experience with marketing data pipelines (Google Ads, Meta, TikTok)
- Experience building reverse ETL workflows
- Familiarity with data ingestion tools (Fivetran, Daton, Airbyte, etc.)
- Experience implementing AI-assisted data transformation workflows
- Exposure to experimentation analytics (A/B testing frameworks)
We are looking for someone who:
- Understands both technical architecture and business implications
- Can move quickly in a project-based environment
- Thinks in systems, not just SQL queries
- Is comfortable leveraging AI tools to improve speed and efficiency
- Has experience working across marketing, product, and operations data
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