Data Analytics Engineer

AIIR Intelligent HVAC; Bengaluru; On-site; INR 800,000 - 1,200,000; Full time

Job summary

AIIR Intelligent HVAC is looking for a Data Analytics Engineer to join their team in Bengaluru, Karnataka. This role focuses on analyzing high-volume HVAC telemetry, delivering diagnostics and actionable insights to improve system performance.

The ideal candidate must have at least 5 years of experience in data analytics, proficient in SQL, Python, and BI tools. The position includes responsibilities in data engineering and collaboration with cross-functional teams to enhance business-critical KPIs.

Qualifications

• 5 years in data analytics or analytics engineering with time-series or IoT-like data.
• Strong SQL and Python (Pandas/Polars; basic statistical tests, resampling/windowing).
• Hands-on with BI and ability to craft clear, story-driven dashboards.

Responsibilities

• Explore time-series HVAC data and produce diagnostics.
• Define, implement, and maintain core KPIs.
• Build dashboards and reports for performance insights.

Tools

Power BI

Tableau

Python

SQL

Job description

Data Analytics Engineer

Location: Bangalore, KA

Engagement: Fulltime

This position is part of the Intelligent HVAC Systems engineering and product development team. The Data Analytics Engineer will bring data analytics and data engineering fundamentals to work with high‑volume HVAC telemetry to deliver diagnostics, customer‑facing insights, and business‑critical KPIs.

Major Areas of Responsibility

Analytics & Insights

• Explore time‑series HVAC data; produce diagnostics such as equipment efficiency, runtime patterns, short‑cycling, coil/freezing risk, comfort drift, demand response impact, and fault signatures.
• Define, implement and maintain core KPIs (e.g., kWh/ton, runtime per call, temperature delta vs. setpoint, comfort index, energy per degree‑day).
• Build dashboards and reports for product, operations, and customers (e.g., performance baselines, anomaly alerts, weekly summaries).
• Design statistical analyses and A/B‑style comparisons (pre/post maintenance, seasonal comparisons, weather‑normalized consumption).

Data Engineering

• Design scalable schemas for time‑series/telemetry, events, and slowly changing device metadata.
• Build curated feature tables and training datasets for model development (feature engineering, aggregation windows, label generation).
• Implement data quality checks (freshness, validity ranges, unit consistency, missingness, sensor drift detection).
• Collaborate on ingestion/processing pipelines (batch/stream), optimizing cost, latency, and reliability.
• Maintain documentation (data contracts, dictionaries, lineage diagrams).

Collaboration

• Partner with AI/ML engineers, software developers, and product managers to prioritize analytics that move KPIs.
• Translate stakeholder inputs into well‑defined analyses and metrics for product insertion.

Required Knowledge, Skills, Abilities, Education and Experience

• 5 years in data analytics or analytics engineering with time‑series or IoT‑like data.
• Strong SQL and Python (Pandas/Polars; basic statistical tests, resampling/windowing).
• Hands‑on with BI (Power BI, Tableau, or Looker) and ability to craft clear, story‑driven dashboards.
• Experience building clean analytics datasets (e.g., dbt modeling, star schemas, data marts, feature tables).
• Solid understanding of data quality, lineage, and instrumentation for telemetry.
• Comfortable with a modern cloud data warehouse (Snowflake, BigQuery, Redshift, Azure Synapse/Fabric) or lakehouse (Delta/Databricks).

Preferred Qualifications

• Experience with Kamea or similar API‑first IoT device management platforms.
• Comfortable consuming platform REST APIs (Python/SQL pipelines) and handling OAuth2/SSO with role/permission scopes.
• Knowledge of cloud security fundamentals: IAM, RBAC, managed identities, network boundaries, Key Vault (secrets/keys/certs), and encryption.
• HVAC or building systems domain exposure (BMS/BAS, AHUs, VAVs, heat pumps, demand response, maintenance logs).
• Time‑series database experience (Azure Data Explorer, InfluxDB, TimescaleDB, Prometheus, ClickHouse, Spark).
• Streaming/ingestion (Kafka, Azure Event Hubs/IoT Hub, Kinesis, Pub/Sub; stream processing with Flink, Spark Structured Streaming, Azure Stream Analytics).
• Feature store experience (Feast/Databricks), basic MLOps familiarity, data orchestration (Airflow, Azure Data Factory, Prefect, Dagster), dbt.
• Geospatial and weather normalization experience (degree‑days, ASHRAE concepts).
• Statistical techniques: anomaly detection heuristics, confidence intervals, hypothesis testing, change‑point detection.

AIIR Products is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.