Senior Backend Software Engineer

Meltwater is a global leader in media intelligence and social analytics. Our mission is to help businesses make more informed decisions by providing them with actionable insights from the vast ocean of online data. With a diverse and talented team spread across the world, we are committed to driving innovation and pushing the boundaries of what's possible in our field.

Meltwater is looking for a Senior Backend Software Engineer, where you'll play a pivotal role in shaping our tech stack roadmap, leading architecture design, mentoring junior developers, and handling intricate backend task. With a keen focus on industry best practices, you'll ensure our solutions remain at the forefront of innovation.

In this role, you will contribute to designing, developing, and maintaining scalable applications that power Meltwater’s data and analytics platforms. You will work across frontend, backend, databases, and cloud infrastructure to deliver reliable, high-performing, and user-friendly solutions. The ideal candidate should have strong hands-on experience in ReactJS, backend development expertise in Python or Java, and solid database experience with PostgreSQL/MySQL and MongoDB.

Experience with CI/CD pipelines, Docker, cloud platforms, and modern Dev Ops practices is highly preferred

• Design, develop, and maintain highly scalable backend services and APIs using Python.
• Build and optimize microservices that power core platform and product capabilities.
• Design and implement RESTful APIs and backend services to support customer-facing features and internal platforms.
• Develop and maintain event-driven systems using technologies such as Kafka or RabbitMQ.
• Build and maintain large-scale data processing pipelines and backend workflows.
• Design solutions for high availability, reliability, scalability, and observability.
• Work with databases such as PostgreSQL, MySQL, MongoDB, and Redis to support high-performance applications.
• Deploy, operate, and optimize services in cloud environments such as AWS.
• Collaborate with Product Managers, Engineers, Data Scientists, and other stakeholders to deliver high-quality solutions.
• Drive architectural decisions and contribute to the evolution of backend platforms and engineering standards.
• Mentor engineers through code reviews, design reviews, and technical guidance.
• Troubleshoot complex production issues and continuously improve system performance, reliability, and operational excellence.
• Write clean, maintainable, and testable code while following engineering best practices.

• 7+ years of professional experience in backend software development.
• Expert-level proficiency in Python and a strong foundation in software engineering principles, design patterns, and best practices.
• Extensive experience designing, building, and operating large-scale backend systems in production environments.
• Strong experience with RESTful API design, microservices architecture, and distributed systems.
• Deep understanding of scalability, performance optimization, fault tolerance, and reliability engineering.
• Experience with messaging and streaming platforms such as Kafka or RabbitMQ.
• Strong experience with databases such as PostgreSQL, MySQL, MongoDB, and Redis.
• Experience building and maintaining large-scale data processing pipelines and backend workflows.
• Strong experience with AWS and containerized environments using Docker and Kubernetes.
• Experience with CI/CD pipelines, automated testing, monitoring, and observability tools.
• Strong understanding of modern software development practices and cloud-native architectures.
• Strong debugging, troubleshooting, and problem-solving skills.
• Excellent communication and collaboration skills, with the ability to work effectively across cross-functional teams.
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience

• Experience working with Machine Learning systems and integrating ML models into production applications.
• Familiarity with machine learning frameworks such as Scikit-learn, Tensor Flow, PyTorch, XGBoost, or similar technologies.
• Exposure to MLOps practices, model deployment, monitoring, and lifecycle management.
• Experience with Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), or Natural Language Processing (NLP) systems.
• Experience with large-scale data processing frameworks such as Spark, Airflow, Ray, or similar technologies.
• Familiarity with vector databases, semantic search systems, and AI-powered applications.
• Experience working in media intelligence, analytics, SaaS, or data platform environments.
• Contributions to open-source projects, technical blogs, or engineering communities.

• Enjoyflexiblepaid timeoff options for enhancedwork-life balance.
• Comprehensive health insurance tailored foryou.
• Employeeassistanceprogramscovermentalhealth,legal,financial,wellness,andbehaviourareas to ensure your overall well-being.
• Complimentary Calm…