Data Engineering Developer / Développeur En Ingénierie De Données

The Opportunity

We’re the creator of BetterSleep: the app that has helped more than 65 million people sleep and feel better across the globe. We have a sleep tracker, relaxing sounds, guided meditations and sleep stories, all available in over 6 different languages! We set out on a mission to help people change their lives with a better night's sleep. 

Who are we and why should you join us?

• We are taking sleep to the next level. We combine great content, technology, and data-driven product development to constantly learn, iterate, and improve.
• We are relentless in our pursuit of better, always questioning the status quo and discovering new ways to get things done and serve our users;
• Our team is agile and nimble, allowing you to have a huge impact and carve your own path from day one.
• We invest in our team’s well-being and professional development because we know that business and individual growth go hand-in-hand. You will move fast, remain flexible, and be challenged every day. Join us!

What are we looking for?

The Data Engineer will be tasked with building, maintaining, and modernizing data pipelines and infrastructure to support key business decisions, ensuring data availability, accuracy, and timeliness. This role involves implementing comprehensive data quality monitoring, enhancing marketing data pipelines, and supporting the production and maintenance of data science initiatives (such as a recommendation system), all aimed at providing reliable data insights, optimizing data workflows, and ensuring cost-effective data infrastructure management for millions of users.

Responsibilities

• Build, develop and maintain data pipelines using python and SQL, prediction models, dashboards and performance metrics that support key business decisions;
• Lead the maintenance and modernization of our data pipeline/stack;
• Ensure the availability, accuracy, and timeliness of data across the company;
• Implement comprehensive monitoring of the data quality to detect anomalies;
• Collaborate with the user acquisition team, product team, and data scientists to support data-driven decision-making;
• Maintain and enhance our marketing data pipeline to accurately model and measure our performance;
• Support the productionalization and maintenance of scalable recommendation system along with other machine learning models;
• Maintain data infrastructure and ensure cost-effectiveness while supporting millions of users;
• Provide technical guidance and support in the integration of new data sources and the optimization of data workflows.
• Implement good software engineering practices across the data stack (CI/CD, unit tests, etc.)

Outcomes expected:

• Reliable, available, and up-to-date data;
• Orchestrated pipeline;
• Dashboards;
• Cloud Data Infrastructure;
• Analysis, insights and business leverage ;
• Data dictionary, nomenclature and other documentation;
• Clear, complete and concise interpretation of the data.