Data Engineer

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.