Data Engineer

We are fixing that with Supabase as the central warehouse. We need an engineer to build it.
Three things have to be true about your background:

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, PostgreSQL, 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 ENGAGEMENT TERMS Rate: $40 to $50 per hour, based on experience and depth of warehouse ownership Equipment: Bring your own device (BYD) and hardware. We will provide systems access to relevant software systems. WHAT GIVES YOU THE EDGE (PREFERRED)
4 to 8 years of data engineering experience
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