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- Tasks: Lead data management and optimise recommendation systems for our innovative social media app.
- Company: Join Luupli, a socially responsible app focused on equity, diversity, and positive impact.
- Benefits: Equity-only compensation with the chance to shape a growing company and its culture.
- Why this job: Be part of a passionate team creating a platform that empowers creators and businesses.
- Qualifications: Experience in data engineering, SQL, and recommendation algorithms is essential.
- Other info: Work in a dynamic environment with opportunities for personal and professional growth.
The predicted salary is between 36000 - 60000 £ per year.
About Luupli:
Luupli is a social media app that has equity, diversity, and equality at its heart. We believe that social media can be a force for good, and we are committed to creating a platform that maximises the value that creators and businesses can gain from it, while making a positive impact on society and the planet. Our app is still in development, but we are excited about the possibilities it presents. Our team is made up of passionate and dedicated individuals who are committed to making Luupli a success.
About the Role:
We’re seeking a skilled Data Lead with experience in recommendation systems to join our team. This role is pivotal in enhancing our backend systems, managing databases, and optimising 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.
Responsibilities:
- Data and Database Management: Design, optimise, 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 optimise recommendation speed and accuracy. Continuously evaluate recommendation logic to better serve user preferences, ensuring real-time delivery.
- Data Aggregation and Analysis: Aggregate, analyse, 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 Optimization: Identify, troubleshoot, and resolve data handling issues to ensure accurate recommendation delivery. Optimise queries, processing workflows, and containerized 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 containerized environment.
- Familiarity with AWS ECS for container management, including task scheduling and scaling.
- Experience using AWS Event Bridge to trigger workflows or automate tasks in response to application events.
- Analytical skills for data aggregation, querying, and insights generation.
- Strong debugging and optimization skills for handling large-scale data processing in cloud-based environments.
Preferred Qualifications:
- Knowledge of data aggregation pipelines, ETL processes, and data handling at scale.
- Familiarity with additional AWS services (e.g., S3, Lambda) for data storage and event-driven architectures.
- Experience with machine learning libraries or tools used in recommendation systems.
Compensation:
This is an equity-only position, offering a unique opportunity to gain a stake in a rapidly growing company and contribute directly to its success.
Data Lead - AWS employer: Luupli
Contact Detail:
Luupli Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Lead - AWS
✨Tip Number 1
Familiarise yourself with the specific recommendation algorithms mentioned in the job description, such as collaborative filtering and content-based approaches. Being able to discuss these in detail during your interview will show your expertise and enthusiasm for the role.
✨Tip Number 2
Gain hands-on experience with similarity search libraries like Annoy or Faiss. If you can demonstrate practical knowledge of how to implement these tools effectively, it will set you apart from other candidates.
✨Tip Number 3
Brush up on your SQL skills, particularly with PostgreSQL and JSONB. Be prepared to discuss how you've used these technologies in past projects, especially in relation to data management and optimisation.
✨Tip Number 4
Showcase your understanding of AWS ECS and how it relates to container management. Discuss any relevant experiences you have with task scheduling and scaling, as this is crucial for the role.
We think you need these skills to ace Data Lead - AWS
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with recommendation systems, database management, and relevant programming skills. Use keywords from the job description to demonstrate that you meet the requirements.
Craft a Compelling Cover Letter: In your cover letter, express your passion for social media and how your skills can contribute to Luupli's mission. Mention specific experiences that relate to data management and recommendation algorithms.
Showcase Relevant Projects: If you've worked on projects involving recommendation systems or data aggregation, include them in your application. Briefly describe your role and the impact of your work on those projects.
Highlight Your AWS Experience: Since the role involves AWS ECS and other AWS services, emphasise any relevant experience you have with these technologies. Be specific about how you've used them in past roles to manage data and optimise performance.
How to prepare for a job interview at Luupli
✨Showcase Your Technical Skills
Be prepared to discuss your experience with SQL, PostgreSQL, and JSONB in detail. Highlight specific projects where you've implemented recommendation algorithms or optimised data structures, as this will demonstrate your technical expertise relevant to the role.
✨Understand Recommendation Systems
Familiarise yourself with different types of recommendation algorithms such as collaborative filtering and content-based approaches. Be ready to explain how you've used these methods in past roles and how they can be applied to enhance user experience at Luupli.
✨Demonstrate Problem-Solving Skills
Prepare to discuss challenges you've faced in data handling and how you resolved them. This could include debugging issues or optimising queries for performance. Showing your analytical skills will be crucial in proving your fit for the Data Lead position.
✨Align with Company Values
Luupli values equity, diversity, and making a positive impact. Be ready to share your thoughts on these principles and how they resonate with your work ethic. This alignment can set you apart as a candidate who not only has the skills but also shares the company's vision.
