Data Engineer

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

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; 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; Design and maintain the TimescaleDB schema — hypertables, continuous aggregates, retention policies, compression; Build the training data snapshot pipeline — versioned dataset extraction with SHA-256 checksums and manifest tracking; Build the data quality monitoring pipeline — null rate tracking, stale timestamp detection, out-of-range value flagging, schema violation alerting; Build and maintain the CMMS integration — ServiceNow / Maximo API connectors, work order creation, status sync; Build the Prometheus/Grafana metrics export pipeline — platform health metrics, data quality dashboards

Requirements

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; Experience with data quality frameworks and monitoring

Nice to have

Familiarity with OPC-UA, BACnet, or industrial data protocols is a strong advantage