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 What you’ll do: 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.

Requirements

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.