Senior Data Engineer
- Рівень:
- senior
- Джерело:
- djinni.co
Що робити
- Multimodal data and storage
- Build and own the pipelines that take data from our collection services, then process it, enrich it and load it into our data storage at scale.
- Decide how each type of data (text, images, geospatial, time-series) is stored and indexed across relational, columnar, search and other storage, so that it can be queried efficiently together.
- Link data across storage systems so that everything related to the same object can be retrieved quickly and consistently.
- Provide fast, reliable data access for AI engineers, analysts and product services.
Що очікуємо
- 5+ years in data engineering (or backend engineering with a strong data focus), working on production systems that process large data volumes.
- Hands-on experience with several types of storage (e.g. relational, columnar/OLAP, search engines, document stores, object storage) and the judgment to pick the right one for each task.
- Experience working with different data modalities. Text is a must; images and/or geospatial data are a strong plus.
- Experience building large-scale pipelines that are resumable, idempotent and memory-safe.
- A track record of building data platforms and custom solutions yourself, not only working within managed platforms (e.g. Databricks).
Що пропонуємо
- Understanding of knowledge graphs, ontologies, entity extraction, linking or resolution.
- Graph databases or graph modelling on relational or columnar storage.
- GIS tooling (e.g. PostGIS).
- StarRocks, ClickHouse or other MPP engines; Elasticsearch or OpenSearch at scale.
- Kafka or RabbitMQ, Airflow, dbt.
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