Senior Data Engineer

Re-architect ingestion — design and build the replacement for the current endpoint-to-cloud-function-to-streaming-queue-to-ETL-to-warehouse path, moving ingestion natively into each customer's own Snowflake account so the platform's data-sovereignty story is true end to end.

Migrate legacy ETL logic — translate existing transformation logic covering activity, meeting/event, network context, and system metadata data into Snowflake-native pipelines using the right combination of native transformation tooling and orchestration.

Design for per-tenant isolation — build data models and pipeline logic that hold up under a cross-account, multi-tenant distribution model, with tenant boundaries addressed explicitly at the schema, pipeline, and secret-management level.

Work through known technical debt — shared credentials baked into client-side builds, build-time-only configuration with no live tenant provisioning, inconsistent cross-platform data-capture parity — deciding case by case what gets carried forward, redesigned, or retired.

Rebuild the platform's core data model — activity, event, network, and metadata — preserving the analytics the business depends on while moving underlying storage and processing into Snowflake.

Validate against real production data patterns — batch sizes, sync frequencies, offline-queue backlogs — captured during discovery to ensure the new pipeline design holds up under realistic load.

• Document migration decisions clearly enough to be defended internally, to downstream customers, and through a formal marketplace review process.