Cloud Software Developer(Analytics)

About Ubiquiti At Ubiquiti Inc., we create technology platforms for Businesses, Smart Homes, and Internet Service Providers, driven by our goal to connect everyone, everywhere. To date, Ubiquiti has shipped over 100 million devices worldwide, from ISP networking products to next generation of IT solutions. Our growth is made possible by the dedicated team of hundreds behind the scenes. From software developers and product managers to designers and strategists, Team UI is driven to achieve our common goal: Rethinking IT. At Ubiquiti, you’ll heighten your potential and broaden your horizons - all while shaping the future of connectivity. Responsibilities (What he/she will do after joining UI) Design, implement, and maintain cloud-based analytics and data processing services using Golang and AWS technologies. Develop ETL (Extract, Transform, Load) pipelines to process structured and unstructured data at scale. Build scalable, real-time, and batch data ingestion and transformation systems. Collaborate with data engineers, backend developers, and product teams to design data models and analytical workflows. Optimize data processing pipelines for performance, cost, and reliability. Ensure data accuracy, integrity, and security throughout the entire lifecycle. Monitor data pipelines and cloud infrastructure, resolving incidents and continuously improving observability. Contribute to architectural decisions and promote engineering best practices in analytics system design. Requirement (Must-Haves) 3+ years of experience in cloud/backend development with Golang or Python. Hands-on experience building and maintaining ETL pipelines or data processing workflows in production. Strong familiarity with AWS services such as Lambda, S3, Kinesis, Glue, Athena, and RDS. Solid understanding of distributed systems, data streaming, and cloud-native architecture. Proficient in RESTful API development and microservices design. Experience with SQL and schema design for analytics and reporting use cases. Knowledge of version control and CI/CD practices. Bachelor’s degree in Computer Science, Data Engineering, or a related technical field. Strong debugging, analytical thinking, and communication skills. Proficiency in AI development environments (e.g., Cursor, Claude Code) and expertise in AI development techniques, such as Spec-Driven Development, are required. Preferred Qualifications Experience with real-time analytics systems and streaming platforms like Apache Kafka or Amazon Kinesis. Familiarity with data lake architectures, data warehousing, and metadata management. Experience in data quality assurance, validation, and pipeline testing frameworks. Understanding of data governance, compliance, and security best practices. Experience optimizing cloud cost and performance in large-scale analytics environments. Prior work with ML feature pipelines or integrating data with machine learning workflows.