Data Engineer

Expleo; Bengaluru; On-site; INR 2,400,000 - 3,600,000; Full time

Job summary

Expleo invites applications for an experienced Data Engineer / DataOps / IoT Expert in Bangalore. The role involves designing, implementing, and operating an industrial data lakehouse (Spark, Iceberg, MinIO, InfluxDB, PostgreSQL) and building end-to-end data pipelines for ingestion, quality, validation, and governance.

The candidate will deploy data gateways for machine and sensor connectivity and integrate AI components (Qdrant, Neo4j, BrainCube analytics) to enable advanced analytics.

Qualifications

• 8–9 years of experience in data engineering, DataOps or IIoT analytics.
• Experience designing lakehouse architectures with Spark, Iceberg and MinIO.
• Hands-on with data gateways for machines and sensors in industrial environments.
• Strong collaboration with DevOps and analytics teams to deliver reliable data flows.

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.

Skills

Lakehouse streaming

Time-series telemetry

Iceberg-Spark-MinIO

IoT gateways

DevOps collaboration

Tools

InfluxDB

PostgreSQL

Neo4j

Qdrant

BrainCube

Job description

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 thelakehouse+ 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 +MinIOcombo is specific; open-table-format experience really stands out.
• Ask how they'd tame a chatty sensor firehose plus late-arriving data.

Desired skills

• Neo4j /Qdrantis nice-to-have (it feeds the AI/analytics layer), not a gate.