Foundations

The Data Platform teams develop an internal platform to collect, access, and process vast amounts of data from different sources. They also build the Machine Learning platform to optimise and improve ML models' lifecycles. They aim to maintain the highest possible data quality and balance data availability, lateness, completeness, and infrastructure costs.

Compute This team develops a platform that enables other teams to create and execute data processing pipelines. They furnish data processing frameworks, infrastructure, and data warehousing capabilities. The technological foundation encompasses various AWS services (Batch, S3, Glue, EC2), query engines such as Spark (operating on Databricks) and Presto (running on IBM Cloud and EKS), and scheduling capabilities with Airflow. Ingestion This team focuses on the ingestion and storage layers of the Data Lake (S3 & Delta — managed using Terraform) and tuning our Streaming System based on Kafka. Insights This team provides a platform to access data insights. They’re responsible for the technical aspects of our data views: integration of Looker with Data Warehouse, definition and maintenance of incremental data views (using SQL & Python), and data access management solutions. They manage integrations with third-party data providers and build internal tools for Data Analysts. Model Lifecycle This team aims to make ML/AI and data-enabled products easy to scale. They empower data practitioners to run 100+ ML systems affecting Bolt customers in real time. They solve common challenges surrounding machine learning systems by offering a way to experiment, build, train, deploy, and monitor them with ease. Experimentation This team provides easy-to-use tools and guidance to empower product teams to run AB tests and make data-driven decisions, reducing risk and promoting long-term value to Bolt. They build systems to design, schedule, run, and analyse experiments at a large scale, which are used across the whole company to make better product and business decisions.