Data Engineer
- Джерело:
- djinni.co
Що робити
- Architect and own data-heavy backend systems powering real-time attribution, user modeling, and scoring
- Build and evolve client-side tracking pixels (like FB pixel / Amplitude snippet / Heap autocapture) from scratch
- Set up and manage scalable ETL workflows: cleaning, merging, enriching, splitting, transforming across millions of behavioral events
- Lead the build of CDP / CDXP-style data layers to support segmentation, scoring, and activation across channels
- Connect and compose systems using modern low-code / no-code tools (n8n) to accelerate ops
Що очікуємо
- System Design & Data Architecture:
- Designs scalable, event-driven data platforms with strong decoupling, fault tolerance, and horizontal scalability. Builds real-time and batch pipelines using lakehouse architectures and streaming systems (Kafka / PubSub).
- Distributed Data Processing (Spark / BigQuery / Iceberg):
- Expert in large-scale data processing, query optimization, and cost-efficient analytics. Deep understanding of Spark execution, partitioning, and modern table formats (Iceberg / Delta).
- Cloud & Infrastructure (GCP / Kubernetes):
Що пропонуємо
- Fully remote with flexible hours (aligned with EU timezones for syncs).
- Influence on quality strategy across the entire engineering organization.
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