Cloud Application Engineer

Roles and Responsibilities: 

1. Platform Scalability & Workflow Optimization

• Enhance existing software services and tools to simplify workflows and ensure scalability to handle 10x the current IoT data traffic. 

• Implement performance-optimized data pipelines, leveraging stream processing, efficient storage, and distributed systems. 

1. Microservices Architecture Advancement

• Leverage and evolve the current microservices architecture to support modular, maintainable, and extensible development of future applications. 

• Promote containerization and orchestration best practices (e.g., Docker, Kubernetes) for deployment consistency and scalability. 

1. Mentorship

• Mentor junior engineers, fostering a culture of learning, ownership, and technical excellence. 

• Conduct regular knowledge-sharing sessions, code walkthroughs to upskill the team. 

1. Process Improvement & Engineering Culture

• Continuously improve engineering processes around: 

• Code reviews: Focus on quality, readability, and maintainability. 

• Testing: Strengthen unit, integration, and load testing coverage. 

• Documentation: Ensure clarity and completeness for internal and external stakeholders. 

• Hiring: Participate in talent acquisition to build a high-performing team. 

1. Technology Evaluation & Adoption

• Evaluate emerging technologies (e.g., edge computing, AI/ML for anomaly detection, time-series databases) aligned with business goals. 

• Conduct proof-of-concepts and technical feasibility studies to validate new tools and frameworks. 

1. Cross-functional Collaboration & Delivery

• Set aggressive yet achievable timelines for key initiatives. 

• Collaborate closely with hardware, product, and business teams to ensure alignment and timely delivery. 

• Drive end-to-end ownership of features—from ideation to production rollout. 

• Serve as the tech lead for the development squad within an agile framework- fostering engineering best practices, mentoring team members, and ensuring smooth sprint execution without direct people management responsibilities. 

Qualifications & Experience 

Educational Background: 

• Bachelor's or master's degree in computer science, Electronics & Communication Engineering, or a related field. 

Core Competencies: 

• Strong analytical, problem-solving, and communication skills. 

• Proficient in presenting technical concepts to diverse audiences. 

• Hands-on experience with agile methodologies such as SCRUM and Kanban. 

• Self-driven and comfortable working in fast-paced, dynamic environments with minimal supervision. 

Technical Skills 

Must-Have: 

• 6-8 years of hands-on development experience in Python and frameworks like Django, Flask, or FastAPI. 

• Expertise in building scalable data pipelines using tools like Kafka, Airflow, or Temporal. 

• Solid understanding of distributed systems (e.g., Kafka, Cassandra, Druid, CouchDB). 

• Experience with scalable time-series databases (e.g., InfluxDB, TimescaleDB, Druid, TDengine, Timestream, Bigtable). 

• Proficiency in relational databases (PostgreSQL, MySQL) and NoSQL databases (e.g., MongoDB). 

• Experience working on high-throughput systems handling at least 500 million transactions per day. 

• Skilled in designing scalable APIs (REST/GraphQL). 

• Experience with asynchronous task management using Celery. 

• Strong grasp of algorithms and data structures with practical application for performance optimization. 

• Knowledge of SOLID principles and design patterns. 

• Deep understanding of architectural principles includi