Analytics Engineer

About The Position

Join Navan's growing Travel Product Strategy & Analysis team as an Analytics engineer focused on driving strategic product decisions through data-driven insights. You'll be at the center of product investment strategy, working directly with Product Managers, Engineering, Design, Leadership and Data Teams to harness data insights and empower teams to optimize our marketplace and user journey on Navan Travel.

As a key member of our small, high-impact team, you'll own business understanding for our travel platforms and serve as the analytical backbone. You will focus on execution by delivering insights, building dashboards, track metrics, develop models and analyze results. This role combines deep data fundamentals and thorough analytical rigor with strategic product thinking to influence investment decisions.

What You’ll Do

• Work cross-functionally with Product, Engineering, Leadership and Design teams to deeply understand business needs and translate them into data requirements, well-defined metrics, and analytical tools to enable KPI tracking
• Design, build, and maintain scalable, reliable data models and infrastructure to support analytics, operations, and product use cases
• Champion data quality, documentation, and execution to ensure observability and trust across the organization
• Own all data aspects of the flights team line of business
• Spearhead AB testing development and implementation to increase deployment trust.
• Support ongoing and adhoc analyses to ensure business goals are met and to uncover areas of opportunity
  
  

• +6 years in analytics engineering, data engineering, or data analytics, preferably in travel or consumer tech companies
• Technical orientation and proven hands on experience
• Highly proficient in SQL and data modeling for complex analysis across large datasets
• Experience synthesizing complex data into actionable insights by utilizing a full modern data stack (dbt, Snowflake preferred) and data visualization platforms (Thoughspot preferred)
• Ability to balance multiple priorities in a fast-paced, high-growth environment, while working cross-functionally with Product, Finance, Engineering, and GTM teams
• Experience working with data modeling tools such as dbt
• Demonstrated success translating complex business requirements into scalable data solutions
• Knowledge in SaaS terminology and KPIs.
• Strong background in data warehousing concepts, dimensional modeling, and analytics methodologies