Senior Data Analyst, Business Operations

Jobtailor; Northern (KY); Hybrid; USD 90,000 - 130,000; Full time

Job summary

Jobtailor is seeking a data‑centric professional to own internal data across sales, marketing, customer success, finance, operations, and engineering. You will build and operate pipelines from REST APIs, databases, and SaaS tools, and integrate HubSpot with BigQuery.

You will model data in dbt, monitor pipelines and data quality, and deliver dashboards and customer health insights. The role emphasizes collaboration with non‑technical stakeholders and durable, scalable solutions.

Qualifications

• Built, deployed, and operated production data pipelines from REST APIs, databases, and third‑party SaaS tools.
• Production Python: version‑controlled, tested, scheduled, and deployed.
• Engineering fundamentals: Git, CI/CD, cron, and deploying your own code to production.
• Daily use of AI coding tools.
• Experience working with non‑technical stakeholders to scope and deliver analysis.
• Self-directed; able to prioritize work independently as the only business‑side data person.

Responsibilities

• Own all of Nectir's internal-facing data across sales, marketing, customer success, finance, operations, and engineering activity.
• Build and operate a bidirectional HubSpot BigQuery integration.
• Build pipelines from Gong, LinkedIn, GCP and Azure billing, and engineering activity.
• Model data in dbt and monitor pipelines, alerting, backfills, and schema drift.
• Define data structures and data capture standards for buying motions.
• Deliver recurring answers through internal dashboards and reports.
• Report to the Director of Analytics and collaborate with cross‑functional teams.

Skills

Production data pipelines

Python programming

Data modeling

HubSpot integration

Cross-functional collaboration

Tools

BigQuery

Airbyte

HubSpot

Snowflake

Redshift

Databricks

Gong

LinkedIn

GCP

Azure

Job description

Responsibilities

• Own all of Nectir's internal-facing data across sales, marketing, customer success, finance, operations, and engineering activity
• Build and operate a bidirectional HubSpot BigQuery integration
• Build pipelines from Gong, LinkedIn, GCP and Azure billing, and engineering activity
• Use Airbyte where appropriate and write custom pipelines against REST APIs and direct database connections where needed
• Model data in dbt
• Monitor pipelines, configure alerting, perform backfills and deduplication, and manage schema drift
• Define sales and marketing data structures, including accounts, contacts, segmentation, attribution, activity, and product usage
• Establish field-level definitions and data-capture standards for professor-led and instructional-designer-led buying motions
• Enforce data quality with scheduled automated checks
• Reconcile data before publishing
• Work with sales, marketing, and customer success to define questions and prioritize worthwhile requests
• Deliver recurring answers through internal dashboards
• Build customer health scoring
• Model sales forecasts and customer segments
• Track cloud, inference, and vendor spend per customer to calculate margin per customer
• Report to the Director of Analytics and collaborate with sales, marketing, customer success, finance, and operations
• Deliver milestones including production HubSpot BigQuery syncing, documented data models, Gong pipeline, automated quality checks, dashboards, customer health scoring, and margin-per-customer visibility

Requirements

• Built, deployed, and operated production data pipelines from REST APIs, databases, and third-party SaaS tools
• Production Python: version-controlled, tested, scheduled, and 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; able to prioritize work independently as the only business-side data person
• Strong written communication on a remote, async team
• No degree requirements
• Nice-to-have experience with BigQuery or comparable cloud warehouses such as Snowflake, Redshift, or Databricks
• Nice-to-have experience with dbt or comparable transformation frameworks such as SQLMesh or Dataform
• Nice-to-have experience with Airbyte or comparable integration tooling such as Fivetran or Meltano
• Nice-to-have experience with Airflow, Dagster, or comparable orchestration
• Nice-to-have HubSpot or Salesforce data modeling experience
• Nice-to-have forecasting, segmentation, clustering, or churn modeling experience
• Nice-to-have cloud cost analysis experience
• Nice-to-have edtech, higher education, or teaching background
• Interest in growing toward machine learning, statistics, and advanced analysis, or existing ML and DS experience
• Systems-thinking approach and focus on durable solutions
• Meaningful overlap with US business hours

Core Competencies

Demonstrates expertise in building and operating production data pipelines, integrating various data sources, and ensuring data quality and accuracy. Proficient in collaborating with cross-functional teams to deliver actionable insights and maintain data structures that support business objectives.

Highest-signal resume keywords

• Production Data Pipeline Development
• Python Programming
• Data Modeling in dbt
• HubSpot Integration
• Collaboration with Non-Technical Stakeholders

Hard Skills

• Data Pipeline Development
• REST API Integration
• Data Quality Assurance
• Data Modeling
• Cloud Cost Analysis
• Forecasting
• Segmentation
• Clustering
• Churn Modeling
• Version Control with Git

Soft Skills

• Strong Written Communication
• Self-Directed Work Ethic
• Prioritization Skills

Industry Keywords

• EdTech
• Higher Education
• Data Analysis
• Sales and Marketing Data Structures
• Customer Health Scoring

Tools & Technologies

• BigQuery
• Airbyte
• Gong
• LinkedIn
• GCP
• Azure
• HubSpot
• Snowflake
• Redshift
• Databricks