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Metro Bangalore and common Data Engineer title balanced by niche IoT/DataOps stack.
Industrial IoT, lakehouse and domain-specific tooling require strong domain experience, limiting cross-industry transfer.
Mandatory 8–9 years plus specific data lakehouse and IoT tech stack makes filters high.
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Design, implement, and operate industrial data lakehouse systems using technologies like Spark, Iceberg, MinIO, InfluxDB, and PostgreSQL.
Build and maintain end-to-end data pipelines for ingestion, data quality, validation, governance, and machine/sensor connectivity through data gateways.
Deploy and integrate advanced AI components (Qdrant, Neo4j, BrainCube) and optimize data infrastructure in collaboration with DevOps and application teams to ensure clean and reliable data flows for advanced analytics.
8–9 years of relevant work experience in data engineering or related fields.
Onsite work location: Bangalore, India.
Proficient with Spark, Iceberg, MinIO, InfluxDB, and PostgreSQL technologies.
Experience deploying AI components such as Qdrant, Neo4j, and BrainCube analytics integration.
Senior-level data engineer with deep expertise in industrial IoT data systems and data lakehouse architecture.
Experienced in building complex, end-to-end data pipelines and deploying AI-driven analytics solutions in production.
Operationally focused with ability to collaborate effectively with DevOps and application teams for infrastructure optimization and reliable data delivery.