About us: Codvo.ai is a next-gen AI and engineering company helping global enterprises transform through Generative AI, Cloud-native platforms, and Product Engineering. With proprietary platforms like NeIO and Pulse, we’re enabling faster, smarter, and scalable digital transformation for industries including Energy, Retail, Travel, BFSI, and Healthcare. As we gear up to launch new AI-powered products and expand global presence, we are seeking a marketing leader to define how Codvo.ai influences the market, shapes perception, and creates a movement.

Role Summary Owns the data pipeline from BMS ingestion through to the analytics layer. Responsible for data reliability, quality, and the real-time streaming infrastructure that feeds the ML models.

Responsibilities Data Ingestion & Streaming Build and maintain the BMS protocol bridge — OPC-UA, BACnet, and MQTT connectors Implement the MQTT ingestion pipeline — topic subscription, message parsing, schema validation, TimescaleDB insertion Monitor ingestion health — message rates, latency, dropped messages, reconnection logic Implement the tag auto-mapping engine — pattern-based matching, confidence scoring, manual override workflow Build the historian adapter — bulk data extraction from customer historian systems (AVEVA Historian, OSIsoft PI, InfluxDB) for baseline profiling Data Storage & Management Design and maintain the TimescaleDB schema — hypertables, continuous aggregates, retention policies, compression Implement data partitioning strategy — per-tenant, per-site isolation Build the training data snapshot pipeline — versioned dataset extraction with SHA-256 checksums and manifest tracking Manage the MinIO/S3 data lake — dataset storage, MLflow artifact storage, backup strategy Implement data retention and archival policies per customer requirements Data Quality & Monitoring Build the data quality monitoring pipeline — null rate tracking, stale timestamp detection, out-of-range value flagging, schema violation alerting Implement the tag freshness monitor — detect when sensors stop reporting, alert on stale data Build the data lineage tracking system — from raw BMS reading through feature computation through model prediction Monitor database performance — query latency, storage growth, index health, connection pool utilization Integration Build and maintain the CMMS integration — ServiceNow / Maximo API connectors, work order creation, status sync Implement the feedback ingestion worker — poll CMMS for work order outcomes, match to predictions, update ground truth labels Build the Prometheus/Grafana metrics export pipeline — platform health metrics, data quality dashboards

Expected Background 5+ years in data engineering — ETL/ELT pipelines, streaming data, time-series databases Strong Python skills, experience with PostgreSQL/TimescaleDB, MQTT, and message broker systems Experience with Docker, Kubernetes, and CI/CD pipelines Familiarity with OPC-UA, BACnet, or industrial data protocols is a strong advantage Experience with data quality frameworks and monitoring

Note- Please apply via our official careers portal only, as applications sent directly to executives may not be considered.