▪Designs, implements and operates the industrial data lakehouse — Spark, Iceberg, MinIO, InfluxDB, PostgreSQL
▪Builds end-to-end data pipelines: ingestion, quality, validation and governance
▪Implements and maintains data gateways for machine and sensor connectivity
▪Deploys advanced AI components — Qdrant, Neo4j, BrainCube analytics integration
▪Delivers clean, reliable data flows for advanced analytics; optimizes data infrastructure with DevOps and application teams
Responsibilities
- Designs and runs the lakehouse end-to-end data pipelines.
- Owns ingestion, data quality, validation and governance.
- Stands up and maintains data gateways for machines and sensors.
- Feeds clean,
reliable data to the analytics and dashboard layers.
- Works with DevOps to optimize the data infrastructure.
- Must-have: lakehouse streaming, ideally time-series (InfluxDB / IIoTtelemetry) — not just batch BI.
- The Iceberg Spark MinIO combo is specific; open-table-formatexperience really stands out.
- Ask how they'd tame a chatty sensor firehose plus late-arriving data.
Desired skills
- Neo4j / Qdrant is nice-to-have (it feeds the AI/analytics layer), not a gate.
📌 Data Engineer (Bengaluru)
🏢 Expleo
📍 Bengaluru
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