Are you ready to be part of something big? We’re hiring for the Sales Analytics Engineer (Sales Operations BI and Analytics Team) on our Sales Team!
In this role, you’ll engage with key decision-makers, forge impactful relationships with some of the world’s most influential organizations, and directly contribute to the growth of Semrush.

WHY SEMRUSH?

We are a global leader in online marketing technology, meeting market demand with rapid scaling. Don’t miss the chance to join our unstoppable momentum and make history with us!

Some highlights of our success include:

• Semrush named a Leader in The Forrester Wave™: Search Engine Optimization Solutions, Q3 2025
• $400M+ Annual Recurring Revenue
• 118,000+ paying customers worldwide
• 1M+ freemium users
• Exceptional demand for our new Enterprise platform, with deals secured from global giants like P&G, Tesla, FedEx, Samsung, Amazon, and others.

If you’re looking for a role where your impact will be visible and meaningful, we’d love to hear from you.

MINIMUM QUALIFICATIONS

• 5+ years of experience in BI Engineering, Data Engineering, or technical analytics roles.
• Strong proficiency in SQL and DBT with production-level experience building transformation layers.
• Solid Python skills for scripting, data pipelines, and automation.
• Experience working in cloud data platforms, preferably GCP (BigQuery, Cloud Functions, Composer, etc.).
• Comfortable working with REST APIs and integrating external data sources.
• Proven success enabling analysts or data consumers through well-designed and well-documented data infrastructure.
• Understanding of AI/ML fundamentals, and how to support analytics maturity toward intelligent automation.

PREFERRED QUALIFICATIONS

• Bachelor’s degree in a technical field such as Computer Science, Engineering, Mathematics, Statistics, or a related discipline.
• Experience in or adjacent to Revenue Operations, SalesOps, or MarketingOps.
• Familiarity with GTM funnel metrics and performance attribution.
• Experience working with BI platforms (e.g., Tableau) from a data modeling and enablement perspective.
• Exposure to AI tooling or ML-based analytics, such as LLMs, embedded agents, or predictive reporting systems.

• Develop and maintain reliable, scalable data pipelines using DBT, SQL, and cloud-native tools (primarily GCP).
• Serve as the technical point of contact for RevOps analysts, enabling efficient, trustworthy access to core datasets and models.
• Partner with Central BI and Engineering to align on data architecture, semantic models, and platform improvements.
• Build and optimize governed, performant data resources that support advanced analytics across sales and marketing operations.
• Architect and implement revenue data models that span the GTM funnel—from leads to bookings.
• Design and maintain attribution models, enabling accurate multi-touch performance reporting across campaigns and channels.
• Support full-funnel forecasting models, partnering with stakeholders to ensure alignment between pipeline, target-setting, and actuals.
• Integrate external data sources via APIs and automation workflows.
• Use Python for data processing, workflow automation, and regression modelling
• Champion best practices in testing, documentation, observability, and reusability.
• Lay the groundwork for AI-driven analytics, helping RevOps adopt intelligent tooling, embedded insights, and automated recommendations.