Ridecell, Inc. is a leading provider of fleet orchestration solutions for fleet and leasing management. The Ridecell 360 fleet industry cloud provides data-driven intelligence and automation solutions to modernize and optimize fleet businesses. Ridecell 360 uncovers blind spots and orchestrates improvements throughout the business and vehicle lifecycle to enable a superior customer experience.

Today, Ridecell powers some of the most successful fleet businesses in cities across Europe and North America, including Arval, Merchants Fleet and KINTO by Toyota Sweden. Ridecell is headquartered in San Francisco, California, with offices in Tokyo, Paris, Bordeaux, Berlin, and Pune, India.

For more information, visit www.ridecell.com

What You’ll Do

• Own and evolve our data pipelines, from ingestion to transformation and delivery.
• Build and maintain our data warehouse to power dashboards, reporting, and analytics.
• Collaborate with product, engineering, and business teams to understand data needs.
• Ensure our data is reliable, secure, and accurate—at scale.
• Help make data self-serve across the company (we want everyone to be data-literate).
• Explore new tools and build prototypes to improve performance and automation.
• Create and maintain dashboards, ETL jobs, and integrations with analytics tools.

What You Bring

• 2–4 years of experience in a data engineering or related backend role.
• Strong SQL skills and experience working with PostgreSQL, BigQuery, or similar.
• Experience with ETL/ELT pipelines, data modeling, and cloud tools (AWS/GCP).
• Comfortable with tools like dbt, Airflow, Kafka, Spark, or similar.
• Strong programming skills in Python or another scripting language.
• You care about clean code, clear documentation, and reproducible processes.
• Bonus: experience with BI tools (e.g., Tableau, Looker) or exposure to SaaS metrics.
• Experience with dashboard/reporting tools (e.g., Tableau, Looker).
• Exposure to data warehouse planning, geospatial queries, or machine learning concepts.
• Knowledge of columnar storage formats (e.g., Parquet, Avro).
• Bonus: experience with Python, Django or statistical tools (R, MATLAB).

React, GO, Python, Django, PostgreSQL, AWS, GCP Android: Kotlin, Java iOS: Swift AWS Lambda