Senior Analytics Engineer, Revenue Operations

DNSFilter

14h • $130,000 - $170,000

About The Position

DNSFilter’s mission is to protect our customers and partners with products they love to use! We are revolutionizing network security by providing fast, accurate, and reliable threat protection and content filtering. We're a rapidly growing company dedicated to creating a safer internet for businesses and organizations worldwide. Leveraging AI-driven threat intelligence, DNSFilter empowers our customers to proactively block threats before they impact their networks. We foster a collaborative, innovative, and results-oriented culture where every team member contributes to our mission of making the internet safer.
As we continue our product-fueled growth by adding new features and broadening our solution to meet the needs of the global market, it's clear there's a missing piece. That's where you come in!
We’re seeking a Senior Analytics Engineer, Revenue Operations, to own and scale the RevOps data domain. This role sits on the Revenue Operations team, will report to the Senior Director, RevOps, and partners closely with Sales, Marketing, Customer Support, Customer Success, Finance, Product, and the Data Platform team to deliver trusted, analytics-ready data that powers GTM systems, reporting, and decision-making.
This is a senior individual contributor role with deep ownership. You’ll treat the RevOps data domain as a product, not a collection of dashboards—balancing rigor, scalability, and stakeholder alignment in a fast-moving environment.
Eligible candidates have and can work successfully in a small to mid-sized fast-paced, hyper-growth, SaaS start-up or scale-up. This is a full-time role open to candidates in the United States and Canada.
We recognize that people come with a wealth of experience and talent beyond just the technical requirements of a job. If you feel like this job is for you, please apply. We believe diversity of experience and skills, including transferable skills, combined with passion, is a key to innovation and excellence; therefore, we encourage people from all backgrounds to apply to our positions!

Requirements

• 5+ years of experience in analytics engineering or data engineering, specifically supporting GTM, RevOps, or BizOps functions
• Expert dbt knowledge, including advanced use of incremental strategies, snapshotting, and modular project structure—you know when to use a macro and when not to
• Deep proficiency in SQL with experience optimizing queries for modern distributed warehouses (e.g., Amazon Athena, BigQuery, Snowflake), including partitioning and cost optimization
• Hands-on experience designing and maintaining analytics-ready data models and ELT pipelines from application and operational data sources
• Experience implementing or working with semantic layers or governed metrics frameworks (e.g., dbt semantic layer or equivalent)
• A meticulous, almost obsessive approach to data accuracy—you aren’t satisfied until the numbers tie out 1:1 and you can prove it
• Demonstrated ability to reconcile complex datasets across systems and identify root causes of discrepancies
• A strong “do it right” mindset, including the ability to push back on unscalable requests and prioritize durable solutions over short-term fixes
• Understanding of data mesh principles, domain ownership, and the discipline required to maintain a standalone analytics data zone
• Strong communication skills and comfort level in influencing both technical and non-technical stakeholders

Nice To Haves

• Direct experience working on a Revenue Operations team
• Experience supporting Sales, Marketing, Customer Support, and Customer Success analytics
• Experience introducing or maturing a centralized data dictionary and driving organizational adoption of governed metrics
• Exposure to data mesh or domain-oriented data ownership models in production environments
• Experience applying AI-assisted development tools to analytics engineering workflows (SQL, dbt, testing, documentation, refactoring)
• Familiarity with revenue lifecycle metrics (pipeline, conversion rates, ARR/MRR, churn, expansion, forecasting)

Responsibilities

• Own the RevOps Data Domain
• Architect and own the RevOps / BizOps data zone within our Data Mesh, treating it as a product that is high-quality, discoverable, well-documented, and the authoritative source of truth for revenue data
• Establish clear ownership, documentation, and governance for core RevOps datasets and metrics
• Build & Scale Analytics Foundations
• Own the end-to-end design, development, and maintenance of analytics solutions that power downstream GTM systems, reporting, and decision-making
• Partner with the Data Platform (Data Engineering) team to transform data landed from internal databases, third-party APIs, and Airflow-managed pipelines into analytics-ready models
• Develop, optimize, and maintain ELT pipelines using dbt Cloud, transforming PostgreSQL and other source data into analytics-ready datasets in Amazon Athena
• Ensure reliable data availability, performance, and quality within our Athena-based analytics data zone
• Own Data State, History, and Performance
• Lead our approach to capturing data evolution and history, making heavy use of dbt snapshots and incremental models to support point-in-time and trend analysis
• Write performant, cost-aware SQL optimized for distributed query engines (Amazon Athena), including queries operating over tens of billions of rows
• Design models with scalability and maintainability in mind, prioritizing long-term clarity over clever but fragile solutions
• Define, Govern & Operationalize Metrics
• Design, implement, and maintain a semantic layer (e.g., dbt semantic models/metrics) that serves as the authoritative source for business definitions and revenue metrics
• Introduce and steward a centralized data dictionary and metric catalog, ensuring consistent definitions across dashboards, reports, and GTM systems
• Partner closely with RevOps, Finance, Product, and GTM stakeholders to define, govern, and evolve shared metrics—aligning on “what is what” as the business grows
• Act as a trusted arbiter for metric definitions, managing versioning, documentation, and change communication
• Model Revenue Data for Downstream GTM Systems
• Design data models that are consumable by the GTM Systems team for use in downstream operational tools such as Salesforce, Hubspot, and Zendesk
• Expose clean, well-documented datasets and metrics that can be reliably reused across reporting, automation, and operational workflows
• Partner with the GTM Systems team to ensure data models meet operational needs, performance requirements, and system constraints
• Ensure consistency between analytical models and operational system logic, minimizing metric drift between analytics and GTM tooling
• Own BI Reporting & Visualization
• Own the design, development, and ongoing maintenance of RevOps dashboards, reports, and visualizations in our BI tool
• Ensure all reporting is powered by governed, well-modeled, and tested datasets—avoiding one-off queries and metric drift
• Partner with GTM, RevOps, and executive stakeholders to translate business needs into scalable, self-service dashboards
• Continuously audit and improve existing dashboards for accuracy, performance, usability, and clarity
• Define standards and best practices for dashboard design, metric presentation, and reporting governance
• Drive Accuracy, Simplicity & Trust
• Get “down in the weeds” to validate data end-to-end, using SQL, spreadsheets, and source-system analysis to trace and resolve discrepancies
• Uphold a “simplicity at scale” philosophy—choosing readable, maintainable SQL over over-engineered abstractions that accrue technical debt
• Maintain logic at the appropriate layer: when metrics require new or corrected product data, partner with upstream owners rather than introducing brittle downstream workarounds
• Review, audit, and refactor existing dbt models, ELT jobs, and dashboards to improve accuracy, performance, and maintainability
• Enable the Business & Look Forward
• Design, build, and maintain dashboards and reports powered by well-modeled, tested data—avoiding one-off queries and metric drift
• Support the GTM Systems team by ensuring analytics and reporting dependencies are reliable and well-documented
• Leverage AI-assisted development tools to accelerate SQL development, dbt modeling, testing, documentation, and refactoring
• Explore and pilot AI-enabled approaches to improve data quality, observability, and operational efficiency with sound judgment around accuracy and governance
• Establish and promote best practices for data modeling, testing, documentation, and dashboard governance

Benefits

• Pathway to promotion to additional organizational positions and responsibilities based upon results and performance, not just time in the chair. You help us grow, and we will help you grow.
• Passionate and intelligent colleagues who work hard and have a good time doing it
• Paid company-wide week off at the end of each year
• Flexible Vacation Policy
• Awesome company swag
• Full medical, dental, and vision benefits for US, UK, and Canada-based employees
• Full short-term disability and life benefits; available long-term disability
• Retirement savings account options with vested company matching for qualifying employees
• In-person annual gatherings. Last time we all spent a week on a beach in Cancun!

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed