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Employment Type: Full-time Work Arrangement: On-site (Gurgaon), 1 day/week remote Seniority Level: Mid-to-Senior (36+ years) DigitalPaani is a Gurgaon-based water technology company building an end-to-end platform that automates the operation of sewage and effluent treatment plants (STPs/ETPs) across residential, commercial, and industrial sites. Combining IoT sensors, real-time telemetry, and AI, the platform detects inefficiencies and recommends adjustments to chemicals, equipment, and treatment processes, automates equipment control, and manages maintenance, chemical inventory, and regulatory-compliance workflows. Today the platform operates across 95 facilities in India and treats over 90 million litres of wastewater daily, supporting leading industrial players in the country's waterneutrality efforts. About the RoleOwns the movement, structuring, and validation of DigitalPaani's sensor and plant data: the pipelines that feed the semantic graph, the sensorhealth/validation layer, and the datasets that downstream ML trains on. This person makes data trustworthy and queryable at fleet scale they are the connective tissue between raw PLC/MQTT telemetry, the Neo4j graph, ClickHouse, and the APIs that product features read from. ResponsibilitiesWhat they'd own on the current board: IoT sensor uncertainty registry, Data Quality Score computations, cross-sensor + lab validation API/endpoints.GraphDB endpoints for managing IoT metadata, including data ingestion and integration, versioning, materialization of virtual sensors in ClickHouse, and dataquality governance.ETL pipelines for supporting IoTbased ML workflows.Required QualificationsStrong SQL + Python for production data pipelines.Timeseries / IoT data at scale irregular sampling, gaps, sensor drift, resampling, deduplication.A columnar/analytical store, ideally ClickHouse (materialized views, projections, query optimization); Postgres/BigQuery/Snowflake/Influx equivalent acceptable.Pipeline/ETL engineering building reliable, monitored ingestion (batch + streaming), with idempotency and backfill experience.API construction exposing data as clean, documented endpoints (the validation API, graph grouping endpoints).Dataquality / validation mindset has built checks, not just moved bytes: range/threshold logic, crosssource reconciliation, understanding of measurement uncertainty.Cloud data infra on AWS (EC2/S3 at minimum) and comfort in a Git/CIbased workflow.Preferred QualificationsMQTT / NodeRED / edge telemetry exposure.Domain adjacency water/wastewater, process/industrial, SCADA, PLC/Modbus (holding vs input registers).Light MLOps experience MLflow, Sagemaker or similar, model versioning, feature/dataset management.Statistical fluency uncertainty quantification, error bounds enough to build the uncertainty register credibly.Technical Skills RequiredLanguages: SQL, Python (production pipelines).Data stores: ClickHouse (materialized views, projections, query optimization); MongoDB; Neo4j / Cypher (plus).Ingestion sources: PLC/MQTT telemetry; Node-RED / edge telemetry (plus).Cloud & tooling: AWS (EC2/S3); Git / CIbased workflow.APIs: clean, documented data endpoints (validation API, graph grouping endpoints).How to ApplyEmail your CV and a short note on relevant timeseries / pipeline work to the contact below. Employment Type: Full-time Work Arrangement: On-site (Gurgaon), 1 day/week remote Seniority Level: Mid-to-Senior (36+ years) DigitalPaani is a Gurgaon-based water technology company building an end-to-end platform that automates the operation of sewage and effluent treatment plants (STPs/ETPs) across residential, commercial, and industrial sites. Combining IoT sensors, real-time telemetry, and AI, the platform detects inefficiencies and recommends adjustments to chemicals, equipment, and treatment processes, automates equipment control, and manages maintenance, chemical inventory, and regulatory-compliance workflows. Today the platform operates across 95 facilities in India and treats over 90 million litres of wastewater daily, supporting leading industrial players in the country's waterneutrality efforts. About the RoleOwns the movement, structuring, and validation of DigitalPaani's sensor and plant data: the pipelines that feed the semantic graph, the sensorhealth/validation layer, and the datasets that downstream ML trains on. This person makes data trustworthy and queryable at fleet scale they are the connective tissue between raw PLC/MQTT telemetry, the Neo4j graph, ClickHouse, and the APIs that product features read from. ResponsibilitiesWhat they'd own on the current board: IoT sensor uncertainty registry, Data Quality Score computations, cross-sensor + lab validation API/endpoints.GraphDB endpoints for managing IoT metadata, including data ingestion and integration, versioning, materialization of virtual sensors in ClickHouse, and dataquality governance.ETL pipelines for supporting IoTbased ML wo
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