Senior Data Engineer - Equity

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December 24, 2024

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Fortyx

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Fortyx is a company that is currently in a pre-launch phase, inviting users to subscribe for updates. The company has not provided specific details about its products or services yet. It emphasizes the use of cookies to improve website user experience and analyze traffic. The launch is anticipated in 2024.

2 - 10 employees

📋 Description

• We’re seeking a skilled Senior Data Engineer with experience in recommendation systems to join our team. • This role is pivotal in enhancing our backend systems, managing databases, and optimizing recommendation algorithms. • You’ll play a critical role in the architecture and performance of our recommendation infrastructure, ensuring accurate, relevant, and efficient recommendations for our users. • Data and Database Management: Design, optimize, and maintain tables and data structures to support recommendation and trending content data. • Work with structured data storage solutions, including PostgreSQL and JSONB, to manage recommendation and interaction data. • Recommendation Systems: Implement and refine recommendation algorithms (e.g., collaborative filtering, content-based, and hybrid approaches) to enhance relevancy. • Use similarity search libraries like Annoy or Faiss to optimize recommendation speed and accuracy. • Continuously evaluate recommendation logic to better serve user preferences, ensuring real-time delivery. • Data Aggregation and Analysis: Aggregate, analyze, and process user interaction data to support recommendations and trending content. • Design efficient queries and implement aggregation methods to capture relevant data and insights for recommendations. • Debugging and Optimisation: Identify, troubleshoot, and resolve data handling issues to ensure accurate recommendation delivery. • Optimise queries, processing workflows, and containerised services for high performance and scalability within AWS ECS.

🎯 Requirements

• Proven experience as a Data Engineer or Backend Engineer, with a focus on recommendation systems. • Proficient in SQL and database management, especially with PostgreSQL and JSONB for structured data handling. • Solid understanding of recommendation algorithms (collaborative filtering, content-based, hybrid approaches). • Experience with similarity search libraries such as Annoy or Faiss. • Strong programming skills in Python, with experience in building backend logic for data-intensive applications in a containerised environment. • Familiarity with AWS ECS for container management, including task scheduling and scaling. • Experience using AWS EventBridge to trigger workflows or automate tasks in response to application events. • Analytical skills for data aggregation, querying, and insights generation. • Strong debugging and optimisation skills for handling large-scale data processing in cloud-based environments.