Main responsibilities

• Design scalable solutions and deliver code that adheres to the client design principles, coding standards, and engineering best practices.
• Lead the development of core capabilities such as scalable data pipelines, storage/query optimization for big data, data lakehouse implementations, and API-delivered insights.
• Focus on writing well-tested and well-documented code with appropriate unit tests and automated integration tests
• Collaborate with other Engineers, Product Management, QA, and other internal stakeholders.
• Key contributor to our CI/CD implementation.
• Contribute to the creation of technical documentation - both internal technical specifications and external facing API documentation. 

Requirements

• 7+ years of software engineering experience delivering scalable, enterprise-grade features.
• 5+ years of hands-on experience with Python and data-focused libraries/frameworks, including Pandas, NumPy, and PySpark.
• Over 5 years of deep SQL expertise, with a strong track record in writing performant queries, optimizing execution plans, and working with large-scale relational datasets.
• Prior experience designing and managing high-volume, high-throughput data persistence and processing systems and architectures that power applications with over 3 9s of uptime.
• Exposure to CI/CD pipelines, monitoring, and automation frameworks for data pipelines and processing.
• Proven experience to analyze, debug, and solve complex technical problems efficiently.
• Attention to detail and enforcing the highest standards of quality and performance
• Experience with relational databases, and with NoSQL databases (e.g. Elastic Search and MongoDB).
• Experience with cloud platforms (e.g., AWS, Azure) and Cloud native frameworks
• Exposure to full stack programming using C#, NodeJS, and front-end Javascript frameworks are highly desirable.
• Exposure to AI and AI/ML Ops pipelines.
• Excellent verbal and written communication skills. 

About us

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