Data & AI Engineer (Estate Solutions)

What we do matters
Azendian Solutions, an AI, Data Science and Operations Technology company, develops solutions for energy and resource optimisation to achieve a smarterand more sustainable Built Environment by reducing carbon footprint, enhancing resource productivity and operations as well as lowering costs. Our AI-driven solution is game changing in its approach, leveraging on Machine Learning, Data Science, Cloud Computing with Operations Technology engineering systems.

What you will do

• Build and maintain data pipelines to process data from building systems and IoT devices
• Work with real-world engineering data (e.g., equipment performance, energy usage)
• Support development of analytics and AI models for:
• Anomaly detection
• Predictive maintenance
• Performance optimization
• Assist in setting up systems and environments for Databases (SQL), basic server setup (Windows/Linux) and running applications using Docker or microservices
• Use modern tools (including AI-assisted tools) to improve productivity and workflows
• Collaborate with engineering and product teams to deliver real-world solutions

Core Responsibilities

. Data Engineering & Pipeline Development

. Data Integration (BMS / IoT Systems)

. Analytics & AI Enablement

. Data Quality & Performance Optimization

. Collaboration & Delivery

Job Requirements

. Bachelor's Degree or equivalent in Electrical/Electronic Engineering or Computing Engineering, Information Technology or related field.

. Minimum 1 year of relevant experience in data engineering, software engineering, or engineering systems.

. Strong foundation in Python and SQL (MSSQLand/or PostgreSQL).

. Familiarity with data processing, ETL pipelines, or data management concepts.

. Experience or interest in working with real-world data (e.g., IoT, engineering systems, or operational data).

. Knowledge in BMS communication protocols (BACnet and Modbus) is preferred but not required.

. Basic familiarity with system setup (e.g databases, Windows/Linux environment, or Docker) is an advantage.

. Experience with workflow orchestration tools (e.g., Airflow, Prefect) is a plus.

. Exposure to data analytics or machine learning concepts is a plus.

. Familiarity with AI-assisted tools or automation tools is an advantage.

. Strong logical and analytical skills.

. Willingness to learn and work across data systems, and AI domains.

. Able to work comfortably and independently in a fast-paced environment.