Customer Success Manager

Event Forwarding UI is now generally available: real-time data delivery, simplified. Today Snowplow is excited to release its self-service Event Forwarding UI - an enhanced capability within Snowplow's Customer Data Infrastructure (CDI) that enables teams to deliver behavioral data to downstream tools in real time. With this release, you can now configure and manage setups directly from the Snowplow Console, starting with out-of-the-box destinations for Braze and Amplitude, with more to come soon. Event Forwarding allows data and analytics teams to act on behavioral data as it happens, powering campaign triggers, real-time analytics, and event-driven operations without adding new infrastructure or introducing latency. Why use Snowplow for real-time Event Forwarding. As customer experiences become increasingly dynamic, the ability to operationalize data in real time has become a critical capability for modern data teams. Until now, this has required trade-offs between speed, governance, and operational overhead. * Batch-based reverse ETL tools, which introduce sync delays that make real-time activation difficult. * Server-side tag managers or custom APIs, which are complex to deploy and difficult to maintain. * Packaged CDPs, which abstract away control, reducing flexibility and trust in the underlying data. Event Forwarding eliminates these trade-offs by extending Snowplow's trusted, scalable pipeline directly to your operational tools, all from within your own managed cloud environment. The result: a faster, more controlled way to power real-time operations and analytics. What's available. 1. Self-Service Configuration in the Snowplow Console Create and manage data forwarding workflows directly in your Snowplow environment, removing the need for Google Tag Manager (GTM) Server-Side or custom code. Define which events to send, apply transformations, and monitor delivery, all in a few clicks, without having to deploy and manage your own infrastructure. 2. Flexible Transformations to Streamline Connections Give teams the flexibility to shape and filter data using custom JavaScript expressions directly within the Console. Define precise logic for which events to forward, how to map fields to destination schemas, and apply real-time transformations without additional tooling. 3. Out-of-the-Box Destinations for Braze and Amplitude Send enriched behavioral events to Braze for instant campaign and Canvas triggers, or stream real-time data into Amplitude for real-time journey analysis and cohort updates. These integrations are ready to use with minimal setup, bringing immediate value to downstream marketing and product operations. 4. Low-Latency Delivery with Governance Built In Deliver validated Snowplow events to supported HTTP API destinations in real time, with latency measured in seconds from event tracking to delivery. Every event passes through Snowplow's existing governance and schema validation, so teams can trust that data quality, lineage, and compliance are never compromised. Why customers are excited. Early adopters in its design partner program saw immediate impact across key workflows, including: * Real-time campaign and journey triggers: Deliver enriched behavioral events to Braze and Amplitude within seconds, enabling personalized messaging and lifecycle campaigns that react instantly to customer actions. * Smarter analytics and segmentation: Stream high-quality, schema-validated event data into Amplitude for deeper funnel analysis, audience updates, and experimentation - all built on a consistent behavioral data foundation. * Operational efficiency and reliability: Eliminate redundant integrations, manual Lambda deployments, and GTM Server-Side maintenance while improving delivery reliability and reducing ongoing engineering effort. * Unified data quality and governance: Maintain a single, trusted data source across analytics and operational tools, ensuring consistency and compliance from collection through to delivery. Looking ahead. The GA release introduces Braze and Amplitude destinations out-of-the-box. Snowplow is thrilled to extend its real-time pipes to these industry leading solutions, but this is just the beginning of its ecosystem support. Snowplow is already expanding coverage to additional downstream systems across analytics, marketing and advertising, event streaming platforms, and more exciting SaaS destinations. Stay tuned for more releases in the near future! Get started. Event Forwarding is now available for Snowplow BDP Cloud and Private Managed Cloud customers running pipelines on AWS or GCP. Reach out to its team if you would like to see a demo or explore the Event Forwarding documentation to learn more.

Transform event specifications into analysis-ready tables in minutes. Today, Snowplow announces the general availability of automatically generated data models in Snowplow Console. This new capability eliminates the manual SQL work that traditionally sits between event tracking and data analysis, enabling teams to generate optimized, analysis-ready tables directly from their data products. The challenge: bridging the gap between events and analysis. Analytics engineers know the pain well: you've instrumented clean, structured event tracking with rich context entities, but before anyone can analyze that data, someone needs to write complex SQL to filter, join, and flatten it all into usable tables. This manual transformation work creates bottlenecks, slows down insights, and requires coordination between tracking designers and data teams. The solution: Self-Service Model Generation. With autogenerated data models, Snowplow is removing this friction entirely. Now, any data product in your Snowplow Console can be transformed into analysis-ready tables through a guided, no-code workflow. Simply select which event specifications, entities, and properties you want to include, and your Snowplow Console generates optimized models ready to deploy to your warehouse. Key capabilities. * Self-Service Model Generation: A new 'Data Models' tab in every data product provides an intuitive interface for configuring and generating models. The guided workflow walks you through selecting your events, entities, and deployment options, producing production-ready code in minutes. * Flexible Deployment Options: Choose the approach that fits your technical environment and use case. Generate simple SQL views for immediate data access, standalone incremental dbt models for custom implementations, or unified models that integrate seamlessly with Snowplow's existing dbt packages for Unified Digital and Normalize. * Automatic Data Flattening: Say goodbye to nested JSON structures. Generated models automatically expand your event and entity data into individual columns, creating wide tables optimized for BI tools, reverse ETL platforms, and direct SQL analysis. Single entities flatten into columns, while array entities are preserved for flexible unnesting later. * Intelligent Event Filtering: For teams using Snowtype for tracking validation, models can filter by event specification ID to ensure only high-quality, validated data flows through. Teams not using Snowtype still benefit from intelligent filtering logic based on event schemas, entities, and cardinalities to access complete historical data without requiring tracking changes. * Multi-Warehouse Support: Generate models for Snowflake and BigQuery warehouses directly from Console, with Databricks support coming soon. Accelerate time-to-analysis in minutes instead of days! Why this matters. * Accelerate Time-to-Value: The journey from "we need to track this" to "here's the analysis" now takes minutes instead of days! Data products become immediately queryable without coordination overhead or custom development work. * Reduce Technical Debt: Stop accumulating one-off SQL scripts and undocumented transformation logic. Generated models follow best practices for incremental processing, performance optimization, and maintainability. * Democratize Data Access: Product managers and analysts can generate the tables they need without waiting for engineering resources. Analytics engineers can focus on complex modeling challenges rather than repetitive flattening work. Get started today. Automatically generated data models are available now for all Snowplow CDI customers using BigQuery or Snowflake loaders. See its documentation for detailed steps to get started. If you are new to Snowplow and want to learn more, reach out to its team today!