Data Analyst

At Autofleet, we're transforming the way fleets operate by leveraging data, automation, and AI to power smarter mobility. As a Data Analyst, you'll play a key role in shaping product strategy and business decisions by turning complex data into actionable insights. You'll partner with Product, Engineering, and customer-facing teams to build scalable analytics solutions, define success metrics, and uncover opportunities that drive impact across our platform

• →Own the product analytics domain for key Autofleet products and strategic initiatives, with a focus on user behavior and product engagement.
• →Design, build, and own our product analytics infrastructure (event tracking, taxonomy, instrumentation) from the ground up, primarily using Mixpanel.
• →Define and maintain a clean, scalable event-tracking taxonomy in partnership with Engineering and Product.
• →Analyze large-scale product and behavioral datasets to identify trends, opportunities, and business insights.
• →Design, build, and maintain dashboards and reporting solutions using Mixpanel and other modern BI tools.
• →Develop automated data pipelines and analytical workflows using Python and Airflow.
• →Partner closely with Product Managers to define KPIs and metrics (activation, retention, funnels, engagement), measure success, and support product decision-making.
• →Work with customer-facing teams to provide insights and occasionally participate in customer discussions and presentations.
• →Build internal tools and processes that improve data accessibility and operational efficiency.
• →Translate complex data findings into clear recommendations for both technical and non-technical stakeholders.

• →5+ years of experience in Product Analytics, Data Analytics, Analytics Engineering, or a similar analytical role, with a track record of owning product analytics end to end.
• →Hands-on experience building product analytics infrastructure from scratch, including event tracking design and taxonomy — Mixpanel experience required.
• →4+ years of hands-on Python experience in a professional environment.
• →Strong SQL skills and experience working with large-scale datasets.
• →Experience building and maintaining workflows using Apache Airflow.
• →Experience using AI-assisted coding tools such as Claude Code as part of your day-to-day workflow.
• →Experience with BI and visualization platforms such as Looker, Tableau, Power BI, or similar.
• →Strong analytical thinking and problem-solving abilities.
• →Ability to independently lead projects and take ownership from definition through execution, especially in ambiguous, 0-to-1 situations.
• →Excellent communication skills and ability to present findings to diverse audiences.
• →Professional working proficiency in English, both written and spoken.