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2 Days ago

Principal Data Analyst

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Dehra dun, Uttarakhand, India
Information Technology
Other
Storable

Overview

About the Role:

We're seeking a strategic, data-driven professional to lead our Business Analysis initiatives for our Marketplace product within the Self-Storage vertical. This is a 'hands on keyboard' high-impact role that bridges business strategy, analytical rigor, and data visualization —ideal for someone who thrives on translating data into actionable insights that drive performance. As the Principal Data Analyst, you will own our marketplace performance metrics, lead the development of world-class dashboards and reporting frameworks, and partner closely with Product, Marketing, Operations, and Finance teams to inform strategic decisions. You'll drive both hands-on analysis and organizational data literacy while mentoring a team of analysts and collaborating with engineering on data infrastructure.

Key Responsibilities:

  • Own and continuously optimize key Marketplace KPIs (conversion, revenue yield, inventory, pricing, etc.).
  • Serve as the steward of metric definitions and business logic—ensuring consistency, accuracy, and alignment across stakeholders.
  • Have a deep understanding of how to run a BI environment. Proactive, insightful, curious.
  • Build and scale world class self-service dashboards and Tableau reports for internal and executive stakeholders.
  • Lead cross-functional analysis projects to uncover trends, diagnose problems, and identify growth and efficiency opportunities.
  • Translate complex data into clear, actionable insights and concise narratives for business and executive audiences.
  • Drive rigorous SQL-based analysis from raw datasets, ensuring high-quality, reproducible outputs.
  • Guide and collaborate with junior analysts in other groups and collaborate with engineering to shape data pipelines and definitions.
  • Collaborate with cross functional partners and teams (Product,Marketing, Finance, Business Insights) to test hypotheses, evaluate feature/campaign performance, and measure outcomes.
  • Identify data gaps or integrity risks and work with stakeholders to improve reliability and accuracy.
  • Champion a culture of curiosity, experimentation, and evidence-based decision-making.
  • Proactively keep other teams in the loop on new data capabilities unlocked and changes being made.

Requirements:

  • 5-7 years of experience in business analysis, data analytics, or related roles, ideally with at least 2+ years in a leadership capacity.
  • Advanced proficiency in SQL with experience working with complex data models and the ability to query complex relational datasets.
  • Other data engineering experience is a significant plus to facilitate sourcing/formating of data.
  • Deep understanding of performance metrics and business levers in a supply/demand or marketplace environment.
  • Experience leading analytics efforts in partnership with cross-functional teams including Product, Marketing, Finance, and Engineering.
  • Proven track record of developing intuitive, scalable dashboards using Tableau (or similar BI platforms).
  • Strong business acumen with the ability to connect the dots between business objectives and analytical frameworks.
  • Exceptional communication skills with the ability to distill technical findings for non-technical audiences.
  • Capable of influencing and informing executive stakeholders with clear, concise insights.
  • Demonstrated experience owning KPIs, building data products, and drive insights into action in a fast paced environment.
  • Ability to navigate ambiguity, manage and prioritize competing needs, and work cross-functionally.

Preferred Qualifications:

  • Experience in the storage, real estate, or marketplace industries strongly preferred
  • Familiarity with modern data stack tools such as Snowflake, dbt, or similar Experience analyzing marketplace dynamics or supply/demand business models
  • Exposure to experimentation frameworks, A/B testing, or uplift modeling
  • Prior exposure to high-growth SaaS or Marketplace operations
  • Data engineering capabilities—especially in sourcing, transforming, or centralizing disparate datasets.
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