Staff Data Engineer

Moxie

. Own Moxie's data infrastructure end to end, including pipelines, warehouse, and modeling layer .

Posted 10/14/2026full-timeRemote • United States, Canada, Chile, Brazil, Colombia, Dominican RepublicLead💰 $78,000 - $209,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data engineering, including end-to-end data infrastructure management, dbt and SQL modeling, and production pipeline orchestration. Proven ability to collaborate with cross-functional teams and optimize data processes for business-critical applications.

Highest-signal resume keywords

Data Engineering ExperienceDeep Dbt Modeling SkillProduction Pipeline ExperienceStrong Python FundamentalsFluency With AI Tooling

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Dbt ModelingSQL ModelingData Pipeline DevelopmentSchema EvolutionAccrual Accounting ModelingCash Accounting LogicPredictive ModelingPrescriptive ModelingAlerting SetupObservability

Soft Skills

Ownership MindsetCollaboration With Non-Technical PartnersLeadership In Delivery

Tools & Technologies

PostgresSnowflakePrefectAirflowDagsterClaude CodeCursorN8N

Industry Keywords

Data InfrastructureBusiness-Critical DataFinancial Reporting LogicSOPsKPIsFailure TriageInfrastructure PerformanceCost Optimization

Tech Stack

Tools & technologies

AirflowPostgresPythonSQL

About the role

Key responsibilities & impact

Own Moxie's data infrastructure end to end, including pipelines, warehouse, and modeling layer
Partner with Engineering on production schema changes from Postgres to Snowflake
Work with Finance to model accounting logic
Build and maintain data pipelines
Keep business-critical data available for internal teams and practices served by Moxie
Own and evolve dbt models, including financial reporting logic and downstream metric effects
Take over Prefect and Snowflake Openflow orchestration and observability layers
Deliver a high-impact first-quarter project: accrual-basis accounting data model or historical EMR data modeling
Establish SOPs and KPIs for security reviews, schema changes, failure triage, infrastructure performance, and cost
Optimize the stack and build pipelines and models supporting predictive and prescriptive Practice Intelligence
Add safeguards for LLM-generated content in data products

Requirements

What you’ll need

5–10 years of data engineering experience
At least one stretch as an early data hire who took a system from basics to business-critical
Deep dbt and SQL modeling skill applied to business logic
Experience modeling cash vs. accrual accounting, incentive logic, and revenue definitions
Strong Python and software engineering fundamentals
Production pipeline experience with Prefect, Airflow, Dagster, or similar
Experience handling schema evolution from an operational database into a warehouse
Experience setting up alerting and observability
Track record of leading end-to-end delivery with non-technical partners
Ownership mindset about uptime, reliability, SLAs, runbooks, KPIs, and cost optimization
Fluency with AI tooling such as Claude Code, Cursor, n8n, or similar
Ability to articulate where LLMs belong in a data stack and where they need guardrails

Benefits

Comp & perks

Equity of 0.017%–0.023% for Tier 1 (US, Canada)
Modern data stack with AI tooling built into the workflow
Real input on the data roadmap and own career trajectory
Inclusive workplace and interview accommodations upon request