We are seeking an experienced Senior Data Engineer to design, build, and maintain scalable, high-performance data platforms that support analytics and machine learning initiatives. This role requires strong hands-on expertise in modern data engineering technologies and the ability to take end-to-end ownership of data services in production environments. The ideal candidate will collaborate closely with cross-functional teams, contribute to architectural decisions, and ensure the reliability, security, and quality of data across multiple platforms. Mandatory Technical Skills Java Apache Spark AWS RESTful Web Services / APIs Apache Kafka Data Engineering (end-to-end pipeline design and implementation) Key Responsibilities Software Development & Data Engineering Design, build, and maintain scalable data pipelines and software applications using modern engineering practices. Write clean, reusable, and maintainable code by applying standard design patterns and libraries. Refactor and optimize existing codebases to improve performance, scalability, and maintainability. Ensure application quality by applying appropriate testing strategies and adhering to defined test standards. Maintain data security, integrity, and quality in line with established standards and best practices. End-to-End System Ownership Own data services and applications end-to-end, including monitoring application health, performance, and key metrics. Proactively identify and mitigate business continuity risks by implementing best practices and maintaining documentation such as runbooks and operational guides. Apply continuous delivery and experimentation frameworks to reduce risk and incorporate feedback. Independently manage deployment, operations, and production support for data applications. Technical Incident Management Respond to and resolve live production incidents within defined SLAs, minimizing customer and business impact. Perform root cause analysis and implement long-term solutions to improve system reliability. Contribute to post-incident reviews, postmortems, and incident documentation. Architectural Guidance Provide technical guidance to product and engineering teams, ensuring solutions meet functional, non-functional, and architectural requirements. Challenge design decisions constructively and provide context within the broader enterprise architecture. Contribute to defining and evolving target architecture and technical capabilities for data platforms. Software Systems Design Evaluate and recommend architecture solutions considering cost, business needs, technology constraints, and emerging trends. Assess the impact of system changes or new integrations with a high-level understanding of infrastructure and platform architecture. Support business growth and development velocity through prototyping, technical spikes, and technology evaluations. Design solutions that meet current requirements while remaining flexible for future enhancements. Critical Thinking & Problem Solving Identify patterns and root causes in complex technical challenges using analytical and logical thinking. Evaluate ideas, plans, and solutions objectively, incorporating external insights and defining measurable improvements. Clearly articulate technical decisions and their rationale to stakeholders. Continuous Improvement & Quality Identify opportunities for process, system, and performance improvements by reviewing existing workflows and standards. Design and implement improved processes, practices, and standards to enhance business and engineering performance. Guide and mentor junior team members on data quality, security, and engineering best practices. Communication & Collaboration Communicate technical information clearly and effectively to both technical and non-technical audiences. Collaborate with stakeholders to achieve mutually agreeable solutions through clear communication and adaptability. Demonstrate active listening by asking relevant questions and engaging constructively in discussions.