Scalable Cloud data warehouse drives smarter fleet management and mobility insights

A leading provider of shared mobility solutions, enabling cities and operators to deploy and manage smart electric vehicle fleets through a robust, white-label software platform. By combining real-time fleet data, user behavior, and operational performance, they empower sustainable, efficient, and scalable urban transportation ecosystems.

We helped the client to optimize and scale their cloud data warehouse using Amazon Web Services (AWS), Snowflake, and dbt. This modernization effort focused on performance tuning, pipeline reliability, and scalability to support real-time fleet analytics and long-term strategic insights.

Client: A leading provider of mobility solutions
Year: 2023

As the client scaled its operations across markets and partners, the demand for fast, reliable data access increased dramatically. The existing data infrastructure faced growing pressure to handle real-time vehicle data, user behavior analytics, and complex reporting needs.

Performance bottlenecks, slow queries, and fragmented data pipelines limited the client's ability to make timely decisions and deliver insights to customers and internal teams.

Challenge

A cloud-native data architecture was designed and implemented, tailored to the demands of scaling shared mobility platforms. We optimized their data warehouse environment by ingesting data from their operational database and migrating key workloads to Snowflake, leveraging its scalable compute model to handle concurrent queries and complex joins efficiently.

While the initial implementation focused on setting up core infrastructure and data flows, dbt was introduced in a later phase to enhance data transformation, governance, and reproducibility. With dbt, their data team could manage transformation logic through code, enforce automated tests, and track lineage across datasets, critical capabilities for maintaining data quality in a fast-paced environment.

The entire platform was deployed on AWS infrastructure, taking advantage of S3 for data storage and seamless integration between services to ensure flexibility and cost efficiency. To support infrastructure as code and enable automated deployment, Terraform was integrated alongside Git-based CI/CD workflows. This approach allows for consistent and repeatable provisioning of data infrastructure and enables automatic deployment of objects to production environments with full version control.

Solution

Partnership outcomes

Following the optimization, the client achieved significantly faster query performance, enabling near real-time analytics for fleet tracking, usage patterns, and operational KPIs. The new Snowflake-based architecture supported seamless scalability as new cities, users, and vehicles were added to the platform.

With dbt in place, data consistency and trust dramatically improved, reducing time spent on debugging and manual quality checks. Business and technical teams now have self-service access to reliable and well-modeled data, accelerating product decisions, customer reporting, and performance optimization.

By investing in a future-ready cloud data stack, the client is now better equipped to support its mission: powering intelligent, data-driven mobility services that reshape the way cities move.

80%

Faster analytics performance with a modern Snowflake-based architecture optimized for concurrent, real-time workloads.

60%

Reduction in maintenance effort through automated data transformations, testing, and lineage tracking using dbt.

40%

Lower infrastructure costs achieved with AWS-native integration, elastic compute scaling, and Terraform-driven automation.

Partnership outcomes

Following the optimization, the client achieved significantly faster query performance, enabling near real-time analytics for fleet tracking, usage patterns, and operational KPIs. The new Snowflake-based architecture supported seamless scalability as new cities, users, and vehicles were added to the platform.

With dbt in place, data consistency and trust dramatically improved, reducing time spent on debugging and manual quality checks. Business and technical teams now have self-service access to reliable and well-modeled data, accelerating product decisions, customer reporting, and performance optimization.

By investing in a future-ready cloud data stack, the client is now better equipped to support its mission: powering intelligent, data-driven mobility services that reshape the way cities move.

80%

Faster analytics performance with a modern Snowflake-based architecture optimized for concurrent, real-time workloads.

60%

Reduction in maintenance effort through automated data transformations, testing, and lineage tracking using dbt.

40%

Lower infrastructure costs achieved with AWS-native integration, elastic compute scaling, and Terraform-driven automation.

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Businesses generate more data than ever, but without the right strategy it stays fragmented and underused. We build scalable, secure cloud data platforms that turn data into faster, smarter decisions. Contact us to learn more.

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