Remote Senior Data Engineer: Own Multi-Tenant Analytics

Growth Minded; United States; Remote; USD 45,000 - 60,000; Full time

Job summary

Growth Minded is seeking a data engineer to own the data layer under InsightsOS and EngageOS, shaping architecture, pipelines, and analytical models for multi-location brands. You will report to the product lead and collaborate directly with the founder.

You'll work with SQL and Python, dbt, and warehouse tech like BigQuery and Postgres to develop semantic layers, governance, and scalable reporting across clients with 2 to 250 locations.

Qualifications

• 2+ years in data engineering with production analytics ownership.
• Strong SQL and Python, dbt or equivalent transformation framework, warehouse design.
• Experience with semantic or metrics layers and aggregation at scale.
• Practical ML: propensity scoring, forecasting, and anomaly detection.
• Comfortable making architecture calls without a spec handed to you and writing clear technical specs.

Responsibilities

• 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.

Skills

SQL

Python

dbt

Data warehouse design

Orchestration

Tools

BigQuery

Postgres

Job description

Growth Minded is seeking a data engineer to own the data layer under InsightsOS and EngageOS, shaping architecture, pipelines, and analytical models for multi-location brands. You will report to the product lead and collaborate directly with the founder.

You'll work with SQL and Python, dbt, and warehouse tech like BigQuery and Postgres to develop semantic layers, governance, and scalable reporting across clients with 2 to 250 locations.