Senior Backend Engineer

Job Description: As a Senior Backend Engineer focusing on Data Pipelines & APIs, you will play a crucial role in designing, building, and maintaining scalable data pipelines and APIs that drive our AI platforms. Your work will involve leveraging cutting-edge technologies to convert intricate data into actionable insights. Key Responsibilities: - Design and implement scalable data pipelines for processing large-scale datasets - Develop robust RESTful APIs and microservices architecture - Optimize database queries and data processing workflows - Collaborate with AI/ML teams to integrate models into production systems - Ensure system reliability, performance, and security Qualifications Required: - 5+ years of backend development experience - Proficiency in Python, Java, or Go - Experience with data pipeline tools such as Apache Airflow, Kafka, Spark - Strong knowledge of database systems like PostgreSQL, MongoDB - Experience with cloud platforms like AWS, Azure, GCP Nice-to-Have: - Experience with ML/AI model deployment - Knowledge of containerization using Docker, Kubernetes - Understanding of data engineering best practices (Note: The additional details of the company were not mentioned in the provided job description) Job Description: As a Senior Backend Engineer focusing on Data Pipelines & APIs, you will play a crucial role in designing, building, and maintaining scalable data pipelines and APIs that drive our AI platforms. Your work will involve leveraging cutting-edge technologies to convert intricate data into actionable insights. Key Responsibilities: - Design and implement scalable data pipelines for processing large-scale datasets - Develop robust RESTful APIs and microservices architecture - Optimize database queries and data processing workflows - Collaborate with AI/ML teams to integrate models into production systems - Ensure system reliability, performance, and security Qualifications Required: - 5+ years of backend development experience - Proficiency in Python, Java, or Go - Experience with data pipeline tools such as Apache Airflow, Kafka, Spark - Strong knowledge of database systems like PostgreSQL, MongoDB - Experience with cloud platforms like AWS, Azure, GCP Nice-to-Have: - Experience with ML/AI model deployment - Knowledge of containerization using Docker, Kubernetes - Understanding of data engineering best practices (Note: The additional details of the company were not mentioned in the provided job description)