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.