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.