Senior Data Analyst, Business Operations
Confirmed on the employer's own hiring board on Oct 14, 2026. First seen by Alion on Sep 11, 2026.
About Nectir
Nectir is the secure AI infrastructure purpose-built for schools. Nectir AI provides 24/7 personalized learning support grounded in course content, without compromising trust, outcomes, or academic integrity. Nectir AI can be integrated into existing Learning Management Systems and is fully FERPA- and SOC 2-compliant. Trusted by 100,000 students across 100+ campuses, Nectir is backed by independent, peer-reviewed research demonstrating a 7.5% campuswide GPA increase. Nectir has raised $18.5M from leading investors including Rethink Impact, Long Journey Ventures, and Entrada Ventures.
About the role
We know a lot about how students use Nectir. We know much less about our own business: which campaigns influence a deal, how long deals take to close, which institutions are at risk of churning, and what each customer costs us to serve. This role exists to fix that.
You'll own all of Nectir's internal-facing data, from source system to dashboard. That covers sales, marketing, customer success, finance, operations, and engineering activity. You'll build and run the pipelines, keep the data trustworthy, and get it in front of the teams who need it. For the first six months the priority is sales and marketing.
The foundation is in place. Our BigQuery warehouse and dbt project are in production, we use Airbyte for integrations where it fits, and our internal dashboards are a custom Python application rather than an off-the-shelf BI tool. You'll extend that stack, not design it from scratch.
You'll report to the Director of Analytics and work day to day with sales, marketing, customer success, finance, and operations.
What you'll do
Build and operate the pipelines
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.
Own data quality and the data model
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 the teams and deliver the data
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.
Once the foundation is solid
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.
What we're looking for
Must-haves
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.
Nice-to-haves
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.
No degree requirements. What you know and can do matters more than where you learned it.
Success metrics
90 days: HubSpot ↔ BigQuery syncing both directions in production. Sales and marketing data model documented with field-level definitions.
6 months: Gong pipeline live. Automated data quality checks running on a schedule. Sales and marketing dashboards in production. Customer health scoring live.
9 months: Margin per customer visible.
Working at Nectir
We're a startup, which means the work moves fast, but the impact is real. You will not be a small cog in a big machine here, but the one building the machine itself. This is a full-time, remote position, open to candidates in the United States, with meaningful overlap with US business hours.
You'll be one of the few people who can see the whole business at once. We want someone who finds that interesting rather than daunting, and who'll tell us what the data says even when it's inconvenient.
What we offer
Competitive pay
Comprehensive health coverage: medical, dental, and vision (for US-based roles only)
401k with employer match (for US-based roles only)
Unlimited PTO
Equity (stock options)
Flexible, remote-first work environment