Senior Data Engineer

About the role

You'll own the data layer underneath InsightsOS and EngageOS, the products that turn booking, CRM, ad, and financial data from multi-location brands into proactive insights and automated actions. Today that layer is built and maintained by our product lead alongside two full-stack engineers. We need someone who owns it end to end: architecture, modeling, pipelines, and the analytical models on top. You'll report to our product lead and work directly with the founder.

Compensation: $45–60K plus revenue-share bonus (we profit share every month)

What you'll do

• Design and own the semantic layer and aggregation architecture across clients with 2 to 250 locations each.
• Build and maintain pipelines from sources like Mindbody, Zenoti, Boulevard, Mariana Tek, Domo, QuickBooks Online, GA4, Google Ads, Meta, and Klaviyo.
• Develop trend, utilization, and propensity models that power proactive insights and lifecycle triggers.
• Work with Claude Code and AI-assisted tooling as a core part of your workflow, not an afterthought.
• Establish data quality, governance, and row-level security patterns as we move into multi-tenant, franchise-level reporting.
• Self-direct discovery and architecture decisions, and write clear technical specs the rest of the team can execute against.
• Join a daily product sync with the product lead and engineering team.

Who you are

• 2+ years in data engineering with real ownership of a production analytics platform.
• Deep in SQL and Python, strong with dbt or an equivalent transformation framework, warehouse design (BigQuery, Postgres), and orchestration.
• Experience with semantic or metrics layers and aggregation at scale, you've solved the "same metric, different answers" problem before.
• Practical ML: propensity scoring, forecasting, and anomaly detection in a product context.
• Comfortable making architecture calls without a spec handed to you, and communicating clearly across time zones in writing.
• Bonus: multi-location, franchise, or subscription business data; marketing or CRM integrations; multi-tenant SaaS.

Why this role

• Full ownership of a product vertical, not a ticket queue.
• Small team, direct impact, your models show up in client revenue within weeks.
• Build the cross-client data asset that is central to our strategy.