Senior Data Engineer - Contractor

Cars & Bids is where automotive enthusiasts find, engage with, and sell great cars. We’re the fastest-growing online auction platform for enthusiast vehicles from every era, paired with a scaled media business across YouTube, the #1 automotive podcast (THIS Car Pod!), social, and events that reach over 50 million enthusiasts each month. Since launching in 2020, we’ve hosted over 34K auctions and sold more than $740 million in vehicles.

We are looking for an experienced data engineer to support our entire data stack — from ingestion through warehousing, transformation, modeling, and reverse ETL — as our sole dedicated data practitioner, on a part-time retainer basis. 

• Structure: Independent contractor (1099/B2B) on a monthly retainer. You invoice us monthly; you are responsible for your own taxes, equipment, and benefits. This is not a W-2 or employee role, and it does not include company benefits or equity.
• Commitment: Approximately 20 hours per week, retained monthly. We care about outcomes and the running health of the data stack, not hours logged or tickets closed.
• Rate: $80–$120 per hour, depending on experience.
• Autonomy: You set your own schedule and choose your own tools and methods. We'll align on priorities and outcomes; how and when you deliver is yours to run. You're free to maintain other clients.
• Location: Remote. 5 hour overlap with PT working hours for collaboration.
• Term: Ongoing retainer with a clear, mutual off-ramp. We expect a long-term relationship, but either side can adjust or wind down with reasonable notice.

• The full data lifecycle: ingestion (Hevo/OpenFlow), warehousing (Snowflake), transformation (tasks and dynamic tables), light modeling and batch inference, and reverse ETL into our operational tools.
• Turn business questions into trustworthy data products that downstream users — both humans and AI — can rely on without second-guessing.
• Build and maintain the bespoke and SaaS-based syncs that move modeled data from Snowflake into the tools where the business operates (HubSpot CRM, Iterable/Braze, support tools, and others as we grow).
• Keep our feature pipelines fresh, our models trained, and our inference flowing to where it creates business value.
• Navigate ambiguity and make two-way-door decisions quickly using data.
• Make pragmatic build-vs-buy calls and resist tool sprawl. Complexity is a choice, and we choose less of it.
• Maintain Snowflake cost discipline — warehouse sizing, query performance, and refresh cadences are your responsibility.
• Strategically take on good tech-debt and pay it down when business-justified.
• Investigate data quality issues and remediate them at the root.
• Join our team syncs when necessary to align on priorities, surface ideas, and propose solutions.

Required:

• Snowflake practitioner — you have strong opinions about warehouse design, query optimization, dynamic tables, tasks, and cost management.
• Experience owning data ingestion in production (OpenFlow, NiFi, Fivetran, Airbyte, or equivalent flow-based or managed ingestion tools).
• Comfort with the full analytics engineering workflow: modeling, testing, documentation, and exposing trustworthy datasets to downstream consumers.
• Experience building and maintaining reverse ETL syncs, both bespoke (API integrations, stored procedures) and via SaaS tools (Hightouch, Census, native CDP integrations).
• Working knowledge of MLOps fundamentals: keeping training pipelines running, feature tables fresh, and batch inference flowing reliably. You don't need to be an ML researcher, but you need to be the person who keeps models in production healthy.
• Proficiency in SQL and Python.
• Proven experience as the only data person on a team, or clear evidence you'd thrive without a peer in your domain.
• Detail-oriented with excellent analytical and communication skills, including the ability to explain data tradeoffs to non-technical stakeholders.
• Full professional proficiency in English.
• Bachelor's degree in Computer Science, a related quantitative field, or equivalent experience.

Nice-to-have:

• Experience with Snowpark, Cortex, or similar in-warehouse ML capabilities.
• Experience supporting AI-driven analytics workflows (business users querying data via LLMs) and the modeling discipline that makes those workflows reliable.
• Experience in marketplace, e-commerce, or auction businesses.