Source description
About the role
About Axross
At Axross , we develop AI-powered HVAC optimization platforms that help industrial clients, including those in pharmaceuticals, semiconductors, and precision manufacturing - tomonitor, control, and reduce their energy usage. Our systems rely on high-quality, real-time data from IoT devices, sensors and BMS, which power smarter, greener decisions for our clients.
Role Overview
We’re looking for a skilled Data Engineer to build a scalable big data processing platform that enables real-time decision-making and AI-powered automation. You'll design systems that handle large-scale data processing , ensure high data quality , optimizing resource usage and reduce cost , and support cross-functional teams with actionable insights. Your work will directly contribute to improving energy efficiency and improve data visibility with real-time dashboard , all while helping us achieve our mission of making industrial HVAC systems smarter.
Key Responsibilities
Build and maintain scalable big data pipelines that handle large volumes of sensor and control data
Design and operate a real-time data processing system that supports timely decision-making
Integrate Kafka and Spark Streaming for low-latency, event-driven data streaming
Implement cloud-based analytics solutions (AWS, Azure, GCP) to support advanced processing
Develop automated data quality checks to ensure high-quality, validated inputs and maintain the integrity of the data processed through the pipeline
Collaborate with AI engineers, IoT engineers and software teams to support ingestion, model development and analytics
Optimize resource usage to reduce data processing costs and storage costs
Continuously monitor, test, and tune systems for performance, cost-efficiency , and reliability
Implement and maintain metadata management
Who We’re Looking For
3–6+ years of experience in big data engineering or data infrastructure roles
Hands-on expertise in large-scale data processing , ETL pipelines, and cloud-based storage
Expertise in Spark , Python and SQL
Experience in Spark Streaming, Kafka, Delta Lakehouse, Databricks (DLT) and Azure Synapse
Experience in data visualisation (eg. Apache Superset, Tableau and Power BI.)
Experience with version control system (Git)
Solid background in cloud computing (AWS, GCP, Azure) and scalable infrastructure
Strong understanding of data quality systems and schema validation
Proven track record of delivering efficiency improvements (e.g., 40%+ in data processing)
Ability to work across engineering and AI teams to deliver clean, production-ready data
Why Join Axross?
Drive real energy impact through data in mission-critical industrial settings
Be part of a team focused on optimizing HVAC performance with AI, IoT, and automation
Work on systems that process large industrial data and power live decision-making
Help us significantly reduce client costs and energy waste through smart tech
Enjoy a collaborative, fast-moving environment with growth and learning opportunities
Competitive salary, flexibility, and the chance to shape the future of smart buildings
Apply Now!
If you're passionate about data infrastructure, energy optimization , and smart automation, we want to hear from you.
More at Axross