Principal Software Engineer Data Platform Engineering

We are enabling the transformation of how energy and water are managed. As part of this mission, we are investing in cloud-native data platform technologies that power intelligent analytics at scale — particularly for large IoT data workloads. We are looking for a Principal Software Engineer - Data Platform Engineering with a strong background in data engineering to help design, build, and scale our next-generation data platform and services. This role will focus on developing performant, scalable, and secure data analytics and data pipelines using Python, Apache Spark, Databricks, and Azure-native technologies. The ideal candidate is passionate about working with large-scale datasets, understands Spark query execution plans, and has experience deploying infrastructure using Terraform and container technologies like Docker.\n\nResponsibilities : \nDesign and implement scalable data pipelines for high-volume IoT telemetry data using PySpark, Spark SQL, and Databricks^Analyze and optimize Spark jobs using execution plans, caching strategies, and memory tuning^Develop Python-based micro-services and reusable libraries to support data processing workflows^Work in a DevOps-driven Agile / Scrum environment to deliver high-quality code in fast iterations^Collaborate with product managers, data scientists, and software engineers to define system requirements and data integration needs^Build and manage infrastructure as code using Terraform to deploy workloads on Azure^Create CI / CD pipelines for deploying and testing data workflows and services^Package and deploy applications in Docker containers and manage runtime environments^Apply strong testing practices, including unit tests, integration tests, and test automation^Participate in architectural discussions and technical design reviews^Ensure secure, reliable, and cost-effective operation of data workloads on cloud platforms