Senior Data Analyst, Business Operations

Nectir provides secure AI infrastructure for schools, delivering personalized learning support while maintaining trust, outcomes, and academic integrity. The Senior Data Analyst will own the company’s internal data systems, building and operating pipelines, enforcing data quality, developing dashboards, and delivering analytics for sales, marketing, customer success, finance, and operations.

Responsibilities:

• Build and own a bidirectional HubSpot ↔ BigQuery integration so the CRM and the warehouse agree
• Build pipelines from the rest of the stack: Gong, LinkedIn, GCP and Azure billing, and engineering activity. Use Airbyte where it works and write custom pipelines against REST APIs and direct database connections where it doesn't. Model the results in dbt
• Operate them: monitoring, alerting, backfills, deduplication, and schema drift. Jobs run on GitHub Actions against incremental dbt models
• Define how sales and marketing data is structured: accounts and contacts, segmentation, attribution, activity, and product usage, down to field definitions and how each is captured. This includes the split between our two buying motions, professor-led adoption and instructional-designer-led adoption
• Enforce it with automated checks that run on a schedule, and hold the standard when someone asks for an exception
• Reconcile before you publish. A silently wrong number is worse than a missing one
• Work with sales, marketing, and customer success to turn requests into defined questions, and push back on requests that aren't worth building
• Land recurring answers in our internal dashboards so teams pull their own numbers
• Build customer health scoring that customer success works from, early enough to act on
• Model sales forecasts and customer segments once the underlying data supports it
• Track cloud, inference, and vendor spend per customer so we know margin per customer

Requirements:

• • Built, deployed, and operated production data pipelines from REST APIs, databases, and third-party SaaS tools
• • Production Python: version-controlled, tested, scheduled, deployed
• • Engineering fundamentals: Git, CI/CD, cron, and deploying your own code to production
• • Daily use of AI coding tools
• • Experience working directly with non-technical stakeholders to scope and deliver analysis
• • Self-directed. You'll be the only business-side data person and will prioritize your own work
• • Strong written communication on a remote, async team
• No degree requirements. What you know and can do matters more than where you learned it
• This is a full-time, remote position, open to candidates in the United States, with meaningful overlap with US business hours
• • BigQuery or a comparable cloud warehouse (Snowflake, Redshift, Databricks)
• • dbt or a comparable transformation framework (SQLMesh, Dataform)
• • Airbyte or comparable integration tooling (Fivetran, Meltano)
• • Airflow, Dagster, or comparable orchestration
• • HubSpot or Salesforce data modeling
• • Forecasting, segmentation, clustering, or churn modeling
• • Cloud cost analysis
• • Edtech, higher education, or teaching background
• • Interest in growing toward machine learning, statistics, and advanced analysis. Or, existing ML and DS experience
• • A systems-thinking approach: you care how the pieces fit together and build things meant to last