Senior Analytics Engineer

SpringTime Ventures; Austin (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

ClearJet is an AI-driven logistics company building the analytical backbone for cost, revenue, SLA performance, and weekly reporting for customers and finance. You will own entire data domains end-to-end, from stakeholder conversations to modeling, pipelines, and the finished dashboards or invoice files the business relies on.

You will join a small team that ships code in your first week, operates with high autonomy, and uses AI agents to multiply impact across messy, real-world data surfaces

Qualifications

• 5–8 years of experience in analytics engineering or data engineering.
• Expert SQL and dbt experience.
• Strong Python skills with production-grade code.
• Ability to work with AI agents as a force multiplier.

Responsibilities

• Own end-to-end data domains from stakeholder conversations through modeling, pipelines, dashboards, or invoice files.
• Maintain and extend dbt models in Snowflake with testing and reconciliation.
• Collaborate with Finance and Operations to tie activities to costs and revenue metrics.
• Automate workflows with AI agents and review their outputs for accuracy and reliability.

Skills

SQL

dbt

Python

Stakeholder mgmt

AI agent automation

Tools

Snowflake

Airbyte

Looker

Job description

ClearJet is an AI-driven logistics company moving e-commerce packages from origin to doorstep — air cargo, ground, sortation, and final mile — for customers like Quince, Fanatics, and Walmart. The Data team owns the analytical backbone of the business: cost, revenue, SLA performance, and the reporting our customers and finance team depend on every week.

The Role

You’ll be the third member of a small, unusually high-leverage data team. We operate AI-natively — agents run our invoice pipelines, monitor our dbt jobs, and self-heal the data platform — which means one engineer here ships what a team of five ships elsewhere. You’ll own entire domains of the data function end-to-end: from a stakeholder conversation, through modeling and pipeline work, to the finished dashboard, analytics, or invoice files the business runs on. You will not be handed tickets; you’ll be handed problems.

What the Data Team Owns

• Cost data (COGS) operations: our vendor-invoice pipeline ingests and reconciles invoices from dozens of air, ground, sort, and final-mile carriers to the penny. We own day-to-day operations, new vendor onboarding, and the credits/disputes workflow — including working directly with Finance and Operations to tie real world activities to costs and related packages.
• Customer reporting & invoicing: the weekly invoice and business-review automation for our customers. We own the domain and the stakeholder relationships behind it.
• Revenue & margin modeling: build our per-customer P&L (gross revenue → net revenue → take rate → gross margin) into finance-blessed, investor-ready models in our data warehouse and BI layers.
• The dbt layer: staging → intermediate → mart models in Snowflake, with a testing and reconciliation culture where "the numbers tie to the source, exactly" is the definition of done.

What We're Looking For

• 5–8 years in analytics engineering, data engineering, or adjacent — with at least some of it at a company where real money flowed through your models (billing, payments, marketplace, logistics).
• Expert SQL and deep dbt experience: incremental models, testing strategy, warehouse performance.
• Solid Python — you've built and maintained real programs (parsers, API integrations, validation harnesses), not just notebooks.
• You work with AI agents as a force multiplier. You direct them, review them, and build automation around them. This team's output depends on it, and we screen for it.
• You can run a stakeholder relationship solo: gather requirements from non-technical partners, push back when the ask is wrong, and present results without an interpreter.
• You like messy operational domains. Vendor file formats change without notice, customer shipping and billing requirements are unique, multiple sources of information exist and finding the “truth” of what happened and why is not always clear. This energizes you rather than frustrates you.

Nice to Have

• Snowflake specifically; Airbyte or similar EL tooling.
• A BI semantic layer (Omni, Looker, or similar).
• Freight, parcel, or supply-chain domain exposure.
• Finance-adjacent fluency: you can read a P&L and hold your own in a conversation about accruals.
• Embedded Analytics implementation for customer-facing apps including SSO, access control, and custom content management.

How We Work

Small team, high trust, high autonomy. Linear for work tracking, everything ships through MRs, agents handle the repetitive work so humans handle the judgment calls. You’ll ship code in your first week, be autonomous on your first domain within 90 days, and own multiple domains within six months.

ClearJet is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, genetic information, or any other characteristic protected by law.