Full Stack Engineer
- Джерело:
- djinni.co
Що робити
- Build and own services across the pipeline — ingestion API, validation, stream processing, adapters, serving API.
- Write dbt models that turn raw events into trustworthy sessions, KPIs, and attribution (session stitching, credit assignment, before/after reporting on merchandising changes).
- Build the browser-side tag and the validation tooling that tells an implementation engineer exactly which events are missing or malformed.
- Build the UI layer — dashboards and embedded analytics — on top of the data you modelled.
- Make it operable: idempotent ingest and replay, deduplication, provenance, tracing, data-quality checks, tenant isolation, GDPR handling.
Що очікуємо
- Project
- A SaaS-based, data-driven eCommerce platform built on AI-powered, fully cloud-native technology for the North American market.
Що пропонуємо
- Snowflake and dbt.
- Azure (also GCP/AWS — we're multi-cloud by design).
- Looker or another semantic/BI layer, embedded analytics.
- Clickstream or product analytics work: beacons/tags, sessionization, attribution models.
- E-commerce, search, recommendations, or merchandising domain experience; Shopify integrations.
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