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 analytics domain for key Autofleet products and strategic initiatives.
• Analyze large-scale operational and product datasets to identify trends, opportunities, and business insights.
• Design, build, and maintain dashboards and reporting solutions using modern BI tools.
• Develop automated data pipelines and analytical workflows using Python and Airflow.
• Partner closely with Product Managers to define KPIs, 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.
• Utilize modern AI-assisted development tools (such as Claude Code) to accelerate analysis, automation, and development workflows.
• Translate complex data findings into clear recommendations for both technical and non-technical stakeholders.

• 5+ years of experience in Data Analytics, Product Analytics, Analytics Engineering, or a similar analytical role.
• 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.
• Excellent communication skills and ability to present findings to diverse audiences.
• Professional working proficiency in English, both written and spoken