Data Engineer

• You have built production ETL or ELT pipelines against real business systems. Commercial APIs, rate limits, schema drift, and jobs that keep running when a vendor changes a field without telling you.
• You have owned a warehouse, not just queried one. Supabase, Postgres, BigQuery, Snowflake, or AWS. You know why a schema decision made in week two costs you in month six.
• You can hand your work to a business user. Enough BI fluency in Metabase, Tableau, or Power BI to model data so it is usable downstream, and you document without being chased.

WHAT SUCCESS LOOKS LIKE Success Outcome #1: Stand Up our Database as the Single Source of Analytical Truth

• Design and build the Supabase schema: staging, core, and reporting layers, with documented relationships
• Model entities that live across multiple systems (client, funnel, role, candidate, transaction) into one consistent definition
• Build data quality checks that catch duplicates, orphaned records, and failed loads before a human finds them in a report
• Keep the architecture tool independent. If TCC swaps an ATS in two years, the warehouse survives it

Success Outcome #2: Connect the Stack and Keep the Pipes Clean

• Build and maintain pipelines from HubSpot, Loxo, Airtable, Ramp, and additional sources as scoped
• Handle incremental loads, backfills, and historical snapshots so we get time series, not just current state
• Build monitoring and alerting so a broken sync surfaces immediately with a clear failure reason
• Consolidate with existing Make.com middleware rather than layering another system on top

Success Outcome #3: Build the Calculation Layer That Turns Records Into Metrics Raw rows do not run a company. You mathematicize them into the numbers leadership decides on.

• Build the metric layer: pod and recruiter utilization, funnel throughput, time to hire, client health inputs, revenue per funnel
• Define each metric once, in one place, so two dashboards cannot disagree about the same number
• Model and expose data for Metabase, Tableau, or Power BI, and build the first views leadership needs
• Leave a documented handoff so the next person can add a metric without calling you

• 4 to 8 years of data engineering experience
• Hands-on Supabase or Postgres depth, including Row Level Security
• Prior API integration work with a CRM (ideally HubSpot), a modern ATS (ideally Loxo), and low code tools (ideally Airtable and Make.com)
• Fluency in at least one project management platform: Linear, Jira, ClickUp, Notion, Asana, or Monday.com
• Experience with DBT or a comparable transformation framework
• Proficient in Python or TypeScript for pipeline work
• Bonus: experience in a services, staffing, or recruiting business where utilization and throughput are the core metrics

Pulled from the full job description

• Paid time off, Rate: $40 to $50 per hour, based on experience and depth of warehouse ownership Hours: 10 to 20 per week, flexible, with reasonable overlap into U.S. business hours Term: 90 day initial contract. There is real potential to extend the engagement based on delivery and roadmap. Classification: 1099 independent contractor. No employee benefits, PTO, or company-sponsored insurance. Equipment: Bring your own device (BYD) and hardware. We will provide systems access to relevant software systems.

There are 3.7 million construction companies in America. Most cannot figure out how to hire. The Contractor Consultants solved it and built a fully remote B2B recruitment platform serving construction and trade businesses across the U.S. and Canada. Zero to over $12M in annualized revenue in three years. 80+ people. On track to support 1,500+ clients in 2026, with a goal of empowering 3,000 construction companies by 2030. That growth created a data problem. HubSpot holds the client and revenue picture. Loxo holds the recruiting pipeline. Airtable holds scoring and ticket queues. Ramp holds spend. Make.com moves data between them. Every system is right about its own slice and none can answer a question that crosses two. Today, “what does utilization look like by pod, by month, against revenue” takes a person and a week. We are fixing that with Supabase as the central warehouse. We need an engineer to build it.