Senior Software Engineer
AI Summary
Develop and Optimize Analytics Pipeline:Design, build, and maintain scalable and robust backend systems for our analytics pipeline.Optimize data processing and storage mechanisms for performance and efficiency.Database Management:Implement and manage database solutions to store and retrieve large datasets.Write complex SQL queries for data manipulation and retrieval.Ensure database performance, integrity, and reliability.Data Analytics Integration:Collaborate with data scientists and analysts to
About this role
Develop and Optimize Analytics Pipeline:
Design, build, and maintain scalable and robust backend systems for our analytics pipeline.
Optimize data processing and storage mechanisms for performance and efficiency.
Database Management:
Implement and manage database solutions to store and retrieve large datasets.
Write complex SQL queries for data manipulation and retrieval.
Ensure database performance, integrity, and reliability.
Data Analytics Integration:
Collaborate with data scientists and analysts to integrate advanced analytics and machine learning models into the pipeline.
Develop APIs and services for data access and manipulation.
Performance Optimization:
Monitor and optimize the performance of the backend systems.
Implement caching, indexing, and other optimization techniques.
Quality Assurance:
Ensure the accuracy and integrity of data throughout the pipeline.
Implement automated tests and conduct code reviews to maintain high code quality.
Collaboration and Support:
Work closely with other engineering teams to integrate the analytics pipeline into the broader system architecture.
Provide technical support and guidance on backend and database-related issues.
Requirements
Qualifications:
Bachelor’s/Master’s degree in Computer Science, Engineering, or a related field with 10+ years of experience.
Proven experience as a Backend Engineer or similar role, with a focus on analytics and databases.
Expertise in SQL and database technologies (e.g., MySQL, PostgreSQL, MongoDB).
Strong knowledge of data structures, algorithms, and software engineering principles.
Proficiency in a backend programming language (e.g., Python, Java, C#).
Familiarity with cloud services (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes).
Preferred Qualifications:
Experience with big data technologies (e.g., Hadoop, Spark) is a plus.