Overview:

Data Engineer / DataOps / IoT Expert

8–9 YEARS · 1 FTE · BANGALORE

- 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.

Qualifications:

IIoT, time-series / telemetry data, manufacturing analytics, OEE.

Essential skills:

- 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