RevOps Analytics Technical Consultant

Position Overview

We're looking for a Rev Ops Analytics Technical Consultant, someone who thrives at the intersection of data and business impact. This is a hybrid role combining analytical rigor with operational creativity, ideal for a proactive learner who enjoys digging into complex data challenges and transforming ambiguity into clear, actionable insights.

Your mission is to bridge the gap between raw, messy data and strategic business decisions. You'll work across multiple data types including Sales, Marketing, Customer Success, Product, and Finance to create robust models and deliver executive-ready insights.

You're not just technically skilled; you're driven by curiosity, adaptability, and a passion for continuous learning. You proactively seek solutions, educate yourself on new tools and methodologies, and communicate clearly to stakeholders at all levels.

Mindset:

• Proactive, curious, and self-taught learner—you consistently pursue knowledge independently.
• Comfortable navigating ambiguity, quickly shifting from detailed data investigations to high-level strategic insights.
• Business-minded with a focus on practical outcomes and decision-making impact.

Experience:

• 3–7 years in data-centric roles such as Revenue Operations, Data Analyst, Data Engineer, Analytics Engineer, Product Analytics, or similar positions.
• Hands-on experience managing data from CRM and GTM systems (e.g., Salesforce, Hub Spot).
• Familiarity with core revenue operations tasks: pipeline tracking, forecasting models, funnel analytics, bookings reconciliation, and KPI definitions.
• Strong proficiency in SQL; experience with data tools such as dbt, Looker, Snowflake, Big Query, DuckDB, or Domo.
• Lean Layer is tool agnostic, so we're more interested in people that bring relevant experience regardless of the tool, but most importantly, people that are passionate to learn new tools and concepts on the go.

Skills:

• Ability to audit, design, and debug data pipelines across sales, marketing, and customer success.
• Skilled in modeling and translating complex data into clear, visual insights for non-technical stakeholders.
• Capable of simplifying complex analytics to concise and impactful visuals and narratives.
• Exceptional clarity in writing, presenting, and explaining insights independent of specific tools.

Roles & Responsibilities:

• Investigate and resolve issues in revenue analytics, such as discrepancies in dashboards, KPIs, and pipeline metrics.
• Audit and streamline data flows across various business systems (CRM, data warehouses, BI tools).
• Create and manage lean, sustainable data models that support analytics and decision-making.
• Collaborate closely with Rev Ops, Marketing, Sales, Customer Success, Product, and Finance teams to align and standardize data definitions and metrics.
• Convert strategic business questions into structured analytical approaches.
• Develop concise visuals and metrics that clearly explain complex data insights to executive stakeholders.
• Proactively propose and implement robust solutions to systemic data and analytical issues, prioritizing long-term fixes over temporary patches.

About You:

• You're experienced in navigating complex, ambiguous data environments and thrive when challenged with finding clarity.
• You're comfortable managing end-to-end data processes, from data sourcing and integration to executive reporting and insight communication.
• You've previously held roles that require bridging technical data skills and strategic business thinking.
• You're autonomous, action-oriented, and capable of independently driving projects forward.
• You value simplicity, clarity, and actionable outcomes above technical complexity alone.

Learn more about what it's like to work at Lean Layer here
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For Canadian Residents
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We also invite you to apply for this position but please note that at this time we can only hire those outside of the United States as full-time contractors. If you have any questions about this set up, please don't hesitate to reach out to.