Data Engineer

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

⭐️ Opening line ⭐️

We are looking for an Data Engineer to join our Data Platform (Ingestion) team.

Your mission is to help streamline data access to promote scalability as we transition from a web-centric to a data-centric design within cloud-based micro-services.

🤝 Reporting Structure

• Direct Report : Damien Parent (Lead Data Engineer).

• Collaboration : You will be part of the Ingestion section of the Data Platform team, collaborating within a tech team of 8 people.

🧠 Your missions

• Build and maintain scalable data ingestion pipelines and ETL/ELT processes (from staging to production).

• Contribute to the evolution of our data architecture to improve performance, scalability, and reliability.

• Partner with analytics engineers, data scientists, and business teams to understand and implement data requirements.

• Support and optimize cloud-based data infrastructure (AWS).

• Deploy automated data quality checks and monitoring systems to ensure data reliability.

• Develop and keep up-to-date technical documentation for data processes and systems.

• Investigate and resolve data-related issues to guarantee data integrity across the stack.

🧁 Our Technical Environment

The following is our current stack, we don’t expect you to be an expert in every single tool.

• Languages: Python, Java, TypeScript

• Data Processing: Spark (GLUE), Apache Beam (or Apache Flink)

• Storage & Table Format: PostgreSQL, Apache Iceberg, S3

• Integration & Messaging: RabbitMQ

• Infrastructure & DevOps: AWS, Terraform (IaC), Docker, Kubernetes, GitLab CI

• Analytics & OLAP System : DBT, Cube, Metabase, Athena

• Methodology: Agile (Scrum), Lean management

🥇 Your Profile and Mindset

Experience Profile:

• Seniority & Experience : Intermediate level with 3 to 5 years of hands-on experience in data engineering.

• Sector Experience (Bonus) : Prior experience in the Tech or SaaS sector is a plus.

• Education: Master / Engineer in Computer Science, Engineering, or related field.

• Languages: Fluent in English and French.

Hard Skills:

• Core Engineering: Solid SQL & Modeling skills (efficient schemas) and hands-on experience with Python or Java.

• Cloud Platform : Experience with AWS, GCP, o r Azure is required.

• Data Processing: Proven experience building robust ETL/ELT pipelines (GB/TB scale) with batch / streaming frameworks (e.g. Spark, Apache Beam, Flink, Hadoop) with automated quality checks and proactive monitoring.

• Orchestration : Experience with Dagster or Airflow (or equivalent).

• Experience with Lakehouse or DataWarehouse is a plus (Snowflake, BigQuery, Apache Iceberg / S3).

• Engineering Standards: Ability to apply best practices to build maintainable pipelines while balancing technical debt with feature delivery (balancing speed and code quality).

• AI usage: We value engineers who use AI-assisted tools (Cursor, Claude, Copilot).

• Health & Privacy (Bonus): Interest in healthcare data and familiarity with GDPR/HDS . Previous exposure to FHIR is a plus.

Mindset and Soft Skills:

• Pragmatic & Focused: Able to work in fast-paced environments with a focus on delivering value.

• Autonomous & Self-driven: Comfortable working independently while contributing effectively to cross-functional teams.

• Curious & Adaptable: Eager to learn and develop expertise in emerging data technologies.

A Note on Applying: We know the perfect candidate doesn't exist. If you believe you possess the core required experience and strongly align with this mindset, we highly encourage you to apply.

Recruitment process

1. 📞 1st HR Contact with Astrid (Recruiter) – 45 min (Remote) – Focus on experience and soft skills.

2. 👥 Job Interview with Damien (Lead Data Engineer) – 45 min (Remote) – Focus on technical fundamentals.

3. 🧠 Technical Test / Use Case with Data team members – 1h30 (On-site).

4. 🤖 Fit Interview with the CTO – 1 hour (On-site or remote) – Focus on fit and culture.

🤝 Meet the Team – 30 min (Optional).

📞 Reference Check & Offer (usually follows within 72 hours 🤞).

Depending on your availability, the recruitment process should last less than 3-4 weeks.

General information

💰 Salary

• For this job (CDI), you have a base salary depending on your experience between €55k-60k.

• Eligible for stock option (BSPCEs) according to the company's existing rules

👍 Benefits

• Health care plan: Alan (50% employer)

• Luncheon voucher: 9€ (50% employer)

• Transport: 50% of your pass OR sustainable mobility pass

📍 Remote work & Location

• 3 days per week

• Location: 29 rue du Louvre, 75002, PARIS