Software Engineer II

Design, implement, and maintain distributed data processing systems using state-of-the-art engineering principles. Leverage AI-powered coding tools and practices to accelerate development, ensure code quality, and automate routine tasks. Develop clean, maintainable, and well-documented code with a strong emphasis on unit/integration testing, code reviews, and automation. Build and optimize scalable ETL pipelines for analytics and machine learning applications, using distributed frameworks (e.g., Spark, Hadoop, Synapse). Write advanced SQL for data extraction, transformation, and analysis, ensuring performance and correctness. Collaborate effectively with product, data science, and analytics teams to translate requirements into robust software solutions. Troubleshoot, debug, and proactively improve system reliability and performance. Bachelor's degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience. 4-5 years of professional experience in software engineering, data engineering, or big data platforms. Solid foundation in software design principles, algorithms, and data structures. Hands-on experience with distributed data processing frameworks (such as Apache Spark, Hadoop, or similar). Strong SQL fundamentals and the ability to write complex, optimized queries. Practical experience with AI-powered coding tools (e.g., GitHub Copilot, TabNine, automated code review/analysis platforms). Experience building and maintaining automated test suites, CI/CD pipelines, Observability and code review processes. Excellent problem-solving skills and attention to detail. Strong communication and collaboration skills, with a focus on teamwork and shared ownership. Demonstrated experience leveraging AI tools and technologies to enhance engineering effectiveness, coupled with a strong curiosity and commitment to continuous learning in the field of Artificial Intelligence.