Role Overview

We are expanding our data team and seeking a Senior Data Analyst who can turn data into clarity, decisions, and measurable impact. You are the eyes and ears for your business lines and functional teams. Your mandate is to move Reap from gut feel and partial data to a forward‑looking, evidence‑based view of performance.

You are not a delivery function waiting for a ticket. You are a strategic partner who proactively digs into the data to help stakeholders understand their customer, product, and team. You partner with business leaders to translate their goals into structured analysis, ensuring data directly informs strategy and target‑setting.


Responsibilities:

• Stakeholder partnership & enablement (Relations)

  • Build deep domain expertise: You cannot analyze what you don't understand. Immerse yourself in the business lines (Direct, Connect, CaaS) to anticipate analytical needs before they are requested.

  • Build strong bridges: Cultivate deep, trust-based partnerships with other teams (especially Customer Growth and Product). You need to know their goals as well as they do.

  • Lead enablement: Don't just fish for them; teach them to fish. Lead training sessions, create documentation, and drive self-service analytics so stakeholders can answer their own day-to-day questions.

  • Be a proactive partner: Don’t wait for requests. Go out and talk to stakeholders to validate assumptions, gather context, identify gaps in their understanding, and start and manage new projects to add value.

• Strategic advisory & commercial Impact (Value)

  • Drive decision velocity: Provide clear, actionable insights and recommendations that enable leaders to make better product, operational, and commercial decisions faster.

  • Influence data creation: Work upstream with stakeholders to define what data they should be generating to better run their functions. Don’t only focus on analyzing what is currently available.

• Analysis, modeling & reporting (Technical)

  • Beyond descriptives: Own business performance analysis and expand capabilities into predictive and scenario modeling to help teams see more.

  • Narrative first: Ensure data visualizations tell a story. Translate complex findings into simple, decision-ready messages for non-technical audiences.

• Data quality & continuous improvement (Scale)

  • Fix it at the source: Don't just clean data; identify why it is messy. Partner with teams to redesign workflows if needed to ensure data is clean at the source.

  • Build for the long-term: When answering a question, build the solution (e.g., a reusable model or definition) so that the next person doesn't have to ask it again.

  • Innovate: Stay updated on AI and other technologies to identify practical use cases for Reap.

Mindset and core competencies:

• Hunter, not order-taker: You do not wait for a ticket. You identify the problem and chase the insight.

• Creates scale: enables others to conduct data analysis.

• Influence without authority: You can change the mind of a Product Manager or Head of Sales by presenting insights with clarity, context, and confidence.

• Commercial fluency: You speak the language of the business, not just SQL.

• Reliability: You are rigorous in troubleshooting, debugging, and validating data. Stakeholders must trust your numbers.

• Structural thinking: You can take an ambiguous business problem and break it down into a logical analytical framework.

• Experience: 8+ years of work experience in data and analytics,  insights, or a similar role.

• Technical proficiency:

  • Strong SQL skills

  • Experience with analytics visualization tools such as Looker/LookML or Looker Studio.

  • Familiarity with Snowflake is a plus.

  • Exposure to AI, machine learning, or predictive analytics is highly desirable.

• A Global & Dynamic Team

• Remote Work Friendly

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