Staff Software Engineer - Payment Processing Domain (9-14 yrs)

Job Summary :

As a Staff Software Engineer, you will be responsible for designing, developing, and implementing high performance software solutions in the payment processing domain. You will lead and contribute to the architecture, implementation, and optimization of backend systems. The role requires a deep understanding of modern software engineering practices, distributed systems, cloud technologies, and a strong focus on scalability, performance, and security.

Key Responsibilities :

- Design, implement, and deploy scalable, secure, and high-quality software solutions for payment processing.

- Lead the architecture and design of complex systems, with an emphasis on high availability, fault tolerance, and low latency.

- Develop microservices and distributed systems, ensuring clean, maintainable, and performant code.

- Collaborate with product managers to define technical requirements, user stories, and system features.

- Manage the product backlog by ensuring that tasks are properly scoped, prioritized, and aligned with business objectives.

- Collaborate with Product Owners and other stakeholders to refine and define new features and improvements.

- Oversee and contribute to regular release cycles, ensuring on-time delivery of features and updates.

- Work with cross-functional teams, including product, quality assurance, design, and operations, to ensure alignment and timely delivery of products.

- Maintain clear and timely communication regarding project status, roadblocks, and risks across teams.

- Document design decisions, code architecture, and technical specifications to ensure clarity across teams.

- Promote and uphold engineering best practices, including test-driven development (TDD), code reviews, and continuous integration/continuous deployment (CI/CD).

- Mentor junior and mid-level engineers, providing guidance and support to foster their growth and improve

team performance.

- Ensure that all code follows security and compliance best practices, especially as they pertain to payment processing and sensitive data.

- Identify performance bottlenecks and inefficiencies in the system, proposing and implementing solutions to optimize performance.

- Continuously monitor and maintain high availability of production systems, addressing incidents and root causes of failures.

- Stay up to date with the latest trends in payment technologies, and apply relevant knowledge to improve existing solutions.

Required Skills & Qualifications :

- Strong technical background in software engineering and architecture, with deep expertise in modern programming languages such as Python, Java, or Go.

- 8+ years of relevant software engineering experience, including significant hands-on experience with distributed systems, microservices, and backend technologies.

- Expertise in cloud platforms such as AWS, with strong experience in services like EC2, Lambda, S3, RDS, and DynamoDB.

- Proficiency with container technologies like Docker and orchestration tools such as Kubernetes.

- Experience with Distributed Task Queues such as Celery and RabbitMQ for handling asynchronous tasks.

- Proficiency in working with relational databases (RDBMS/SQL), including database design, optimization, and queries.

- Experience in designing and building scalable, distributed systems with strong knowledge of system design principles, such as high availability, scalability, and fault tolerance.

- Familiarity with CI/CD pipelines and automation tools to streamline the software development process.

- Experience implementing secure coding practices and working with sensitive financial data in the context of payment processing.

Preferred Skills & Qualifications :

- Experience in building systems for payment processing, including working with payment gateways, transaction management, fraud detection, and compliance.

- Familiarity with event-driven systems and tools like Kafka or other event streaming platforms.

- Strong experience in performance tuning and optimizations, especially in high-throughput systems.

- Experience working in Agile teams and familiarity with Agile tools such as Jira, Confluence, or similar.

- Proven experience in leading technical teams, mentoring engineers, and guiding them through technical challenges.