Staff Software Development Engineer

Roles & Responsibilities

• Lead the architecture, design, development, and enhancement of scalable, reliable, and maintainable software products and platforms.
• Design and develop efficient, reusable, testable, modular, and scalable applications and services.
• Design solutions for data-intensive and distributed workloads, including data extraction, processing, transformation, cleaning, enrichment, and delivery.
• Drive product enhancements and new feature development while ensuring alignment with product objectives and long-term technical strategy.
• Apply appropriate design patterns, object-oriented principles, data structures, algorithms, and architectural practices to solve complex engineering problems.
• Conduct code and design reviews, promoting high standards for quality, security, performance, reliability, and maintainability.
• Mentor engineers through technical guidance, design discussions, code reviews, knowledge sharing, and problem solving.
• Improve engineering processes, development practices, automation, and team productivity through continuous improvement.

Requirements

• 9 to 12 years of relevant work experience in software engineering and back-end application development.
• Proven track record of delivering production-grade systems.
• Strong hands-on experience with Python and developing RESTful APIs and backend services using FastAPI or similar frameworks.
• Strong experience designing and implementing micro-services and distributed systems.
• Hands-on experience with containerized application deployment.
• Experience with SQL databases, and NoSQL databases, such as MongoDB, Opensearch/Elasticsearch including indexing, mapping, search, querying, and performance optimization.
• Experience with data extraction, web scraping, data ingestion, cleaning, transformation, processing, and enrichment.
• Strong understanding of API design, service-oriented architectures, integrations, and asynchronous/distributed processing.
• Excellent communication and collaboration skills with both technical and non-technical stakeholders.
• Good to Have:
• Experience applying AI and Machine Learning techniques to data-related problems.
• Exposure to LLMs, Generative AI, embedding, vector search, classification, entity matching, and automated data enrichment.
• Experience with large-scale data platforms, distributed data processing, event-driven architectures, or data pipelines.
• Experience contributing to technical strategy, architecture, and engineering standards across multiple teams.