- Company Name
- Shiftmove
- Job Title
- Senior Sales Data Analyst SaaS (all genders)
- Job Description
-
Job Title
Senior Sales Data Analyst, SaaS
Role Summary
Leverage data science, BI analytics, and SaaS GTM strategy to own and drive the Tableau platform and analytics end‑to‑end for the Revenue Operations team. Deliver actionable insights, forecast performance, and enable data‑driven decision making across sales, marketing, and product functions.
Expectations
- Own and maintain Tableau Desktop, Prep, and Server/Cloud environments, ensuring high‑quality, scalable dashboards.
- Champion Tableau adoption, building trust among executives and front‑line managers.
- Own GTM analytics lifecycle: funnel, pipeline, conversion, churn/retention, ARR, NRR, GRR, LTV, CAC.
- Conduct predictive modeling, cohort analysis, segmentation, and forecasting to inform strategy.
- Translate analytics into concise, story‑driven recommendations for leadership.
- Collaborate with data engineers on pipelines from Salesforce, marketing automation, finance, and product usage; enforce data quality and governance.
- Lead the BI strategy and KPI alignment with GTM priorities; mentor junior analysts.
Key Responsibilities
- Design, build, and govern Tableau dashboards for all GTM stakeholders.
- Optimize dashboard performance and enforce best practices.
- Develop and maintain Snowflake-based data models and dbt pipelines.
- Perform advanced analytics: predictive models, clustering, regression, time‑series forecasting.
- Produce deep‑dive reports on sales trends and key performance indicators.
- Communicate findings via executive briefings, workshops, and written reports.
- Lead cross‑functional initiatives to anticipate data needs and deliver insights proactively.
- Mentor and coach junior analysts on analytical techniques and storytelling.
Required Skills
- 4+ years of BI/Data Science/GTM analytics experience.
- Deep expertise in SaaS go‑to‑market KPIs across the customer lifecycle.
- Advanced Tableau skills (design, performance tuning, governance).
- SQL proficiency; experience with Snowflake or comparable warehouses.
- dbt and modern ELT/ETL tool proficiency.
- Python or R for data analysis, modeling, and automation.
- Applied data science experience (predictive modeling, clustering, regression, time‑series).
- Excellent storytelling and communication with non‑technical stakeholders.
- Leadership experience: leading projects, cross‑functional alignment, inspiring data‑driven culture.
Required Education & Certifications
- Bachelor’s degree in Data Science, Statistics, Computer Science, Business Analytics, or a related field.
- Professional certifications in BI (Tableau Desktop Specialist/Professional), SQL, or data engineering (e.g., Snowflake or dbt certifications) are a plus.