About the role
Data Analytics Engineer at Implicity: job opportunity in Paris Job offers
Who we are Data Analytics Engineer Paris Full-Time Apply Now About Artificial Intelligence & Big Data lead to paramount progresses in Healthcare, and Implicity has a leading position to shape the future of Cardiology. Implicity created a SaaS cloud-based & AI-driven platform, that automates the cardiac remote monitoring of: Implanted devices, like pacemakers, defibrillators, etc. External devices, like weight scales for instance Implicity remote monitoring platform was designed by Dr Arnaud Rosier, cardiologist, to provide hospitals with a complete solution to effectively monitor their patients. Medical teams can now have a far better focus on prevention/treatment, bringing the best care at the best time, instead of struggling in admin/data burden. No other company in the world is able to compete with their: Exhaustive real-time data collection / aggregation across vendors UX design Powerful algorithms, that bring the greatest support to cardiologists for diagnostics The predictive algorithm brings a preventive dimension to the monitoring of cardiac rhythm diseases, heart failure and other cardiovascular diseases. And by avoiding hospitalization, Implicity meets the challenges of healthcare costs control. To put in a nutshell, Implicity saves thousands of lives at a lesser cost… 💓🩺 Job Description
About us 💙 Implicity is a digital MedTech, that brings outstanding innovations to cardiologists, thanks to Big Data and Artificial Intelligence. Thanks to our leading cardiac remote monitoring platform, it’s way easier to manage data and predict patient issues, so that cardiologists can bring the best care at the best time. To put it simply, when you join Implicity, you’ll contribute to save lives with us 💓🩺 Dr Arnaud Rosier (cardiologist and AI researcher) & David Perlmutter (engineer and entrepreneur), co-founded Implicity in 2016. 10+ years later, a French Start-Up / Scale-Up 🐓 is a real game changer in the healthcare market, literally shaping the future of cardiology. 250+ hospitals / medical centers are already using our solutions, covering 100 000+ patients. 👩🏻👨🏿👱🏻 At Implicity, you will find the greatest experts in data science, engineering, clinical, regulatory, IT, sales, customers success, etc. working together. This amazing team already managed to make Implicity a clear European leader, and we will very soon do the same in the US market. In a nutshell, thanks to Implicity: 🏆 Patients get a far better care 🏆 Doctors’ life is far easier, they can have a far better focus on prevention/treatment, and not admin/data burden 🏆 Healthcare payers (Social Security in France) eventually pays a far lower price (preventing/monitoring instead of treating/hospitalizing) It can start as soon as you can! Job and recruitment context As an Analytics Engineer in the Data Team, you will contribute to the design and evolution of analytical pipelines that powers our business stakeholders insights. Your goal in this job is to consolidate our single source of truth, maintaining analytical models, and a data stack that scales with Implicity's growth across Europe. 🤝 Reporting Structure Direct Report: Damien (Data Engineer Manager) Collaboration: You will be part of the Analytics section of the Data Platform team, collaborating within a tech team of 8 people. 🥇 Your Profile and Mindset Experience Profile Experience : 3+ years as an Analytics Engineer or similar data & analytics role Familiarity with Modern Data Stack : data modeling, ETL/ELT, and orchestration tools. Strong interest in the healthcare sector and the challenges of medical data normalization (HL7, FHIR). Strong ownership mindset and attention to data quality. Fluent in English and French. 🧠 Your missions Transformation Pipelines (ETL): Develop and maintain scalable data pipelines ( dbt, Dagster ), comprehensive semantic layer and robust transformation pipelines to convert raw data into analytics-ready datasets. Semantic Layer: Build and maintain business oriented models using cube.dev ensuring BI-ready datasets to access to critical performance indicators. Data Quality & Traceability: Implement automated testing and monitoring to ensure the highest levels of documentation, data quality and availability from S3 to Metabase Stakeholder Partnership: Act as a technical partner to Business Unit teams, translating business questions into technical