DNSFilter · 4 hours ago
Senior Analytics Engineer, Revenue Operations
Tampa, FL
Full-time
Onsite
Senior Level
$130K/yr - $170K/yr
5+ years expDNSFilter is a rapidly growing company dedicated to creating a safer internet for businesses and organizations worldwide. They are seeking a Senior Analytics Engineer, Revenue Operations to own and scale the RevOps data domain, partnering closely with various teams to deliver trusted, analytics-ready data that powers GTM systems, reporting, and decision-making.
Cyber SecurityMachine LearningNetwork Security
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
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
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
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
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 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
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
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
Qualification
Required
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
Preferred
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)
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!
Company
DNSFilter
DNSFilter provides security via DNS that protects over 4M end users from online security threats using artificial intelligence.
51-200 employees
Funding
Current Stage
Growth StageTotal Funding
$62.11MKey Investors
Insight PartnersBigfoot CapitalTechstars
2023-08-10Series A· $15M
2022-08-17Series Unknown· $10.76M
2021-07-21Series A· $30M
Leadership Team
Ken Carnesi
Co-Founder & CEO
Brian Gillis
Co-Founder
Recent News
2026-02-03
2025-12-18
Company data provided by crunchbase