Senior Data Engineer
- Рівень:
- senior
- Джерело:
- djinni.co
Що робити
- Build and own integrations with third-party APIs — REST, GraphQL, webhooks, the occasional CSV drop or legacy SOAP endpoint. Auth flows, pagination, rate limits, retries, backfills.
- Design and run the pipelines that feed the client's AI system: ingestion, normalisation, enrichment, and delivery into the stores it reads from.
- Build the ingestion path for AI workloads — chunking, embeddings, and keeping vector indexes fresh as source data changes, without full re-indexing every time.
- Model the data. Design schemas that hold up as sources are added and change underneath you.
- Make pipelines idempotent, observable, and recoverable. Things will break upstream; the system should degrade predictably and tell you why.
Що пропонуємо
- Hands-on experience feeding LLM or RAG systems — chunking strategies, embedding pipelines, vector stores (pgvector, Qdrant, Pinecone, whatever you've used). Side projects count; commercial experience is not required here.
- dbt, or another transformation layer you've run in anger
- Data quality and observability tooling (Great Expectations, Monte Carlo, or your own)
- Experience with managed connectors (Fivetran, Airbyte) — including knowing when to stop fighting them and write your own
- Early-stage or agency background: greenfield work, shifting requirements, direct client contact
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