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 a Senior Data Engineer to join our Data Platform — Ingestion squad. You will design, build and operate the pipelines that bring cardiac device data into Implicity's platform: around 2 million pipeline executions per day, across approximately 100 pipeline types, serving 250+ hospitals and 100,000+ patients. Our core engineering challenge is reliability and operability at high orchestration cardinality.

As a medical device manufacturer, we operate under regulatory requirements that directly shape how our data platform is designed: traceability, reproducibility and auditability are built-in constraints, and our ingestion pipelines sit on a clinically critical path where reliability has a direct impact on patient monitoring.

Our ingestion stack is currently being modernized: we are progressively replacing our orchestrator, Temporal has recently been selected. You will work on an existing system carrying live clinical traffic, which requires understanding and securing the existing platform before replacing its components.

🤝 Reporting Structure

Direct Report: Damien Parent (Data Manager)

Collaboration: Data Ingestion Squad

🧠 Your missions

As a Senior Data Engineer, you will design, build and operate the ingestion pipelines that feed Implicity's data platform, in a regulated HealthTech environment.

You will:

• Design, build and maintain ingestion pipelines in both streaming and batch modes, from heterogeneous cardiac device sources

• Design, implement and optimize ELT/ETL pipelines for efficient and reliable processing

• Own workflow orchestration: DAG design, retry, replay and backfill strategies, SLA definition

• Design and optimize data models and warehousing (PostgreSQL, AWS Athena or equivalent)

• Ensure data quality, integrity and traceability across pipelines and distributed systems

• Deploy, monitor and operate the pipelines you build, including alerting, incident response and participation in the team's on-call rotation

• Contribute to technical decisions: evaluate and benchmark options, document trade-offs, and support the adoption of the squad's tooling

• Collaborate with Analytics, Product and Engineering teams to enable self-serve, data-driven decision-making

🧁 Our Technical Environment

Our stack is currently evolving. We do not expect expertise on every tool.

• Cloud Infrastructure: AWS

• Architecture: Microservices, event-driven patterns (RabbitMQ)

• Primary Languages / Frameworks: TypeScript (Node.js, NestJS), Python

• Ingestion & orchestration: Transitioning to Temporal

• Analytics: AWS Athena, DBT, Dagster, Metabase

• Containers & Orchestration: Docker, Kubernetes

• CI/CD: GitLab CI

• Observability: Prometheus & Grafana

🏅 Your Profile and Mindset

Experience Profile

• Master's degree in Computer Science, Data Engineering, or equivalent

• 6+ years of experience designing and operating data pipelines in production

• Hands-on experience with both streaming and batch ingestion, from heterogeneous sources and APIs (Kafka, RabbitMQ, Kinesis, Pub/Sub, CDC, Spark, Beam or equivalent)

• Hands-on experience with a workflow orchestrator you have implemented, extended or migrated (Dagster, Temporal, Airflow, Prefect, etc), including retry, idempotency and backfill strategies

• Solid understanding of SQL and NoSQL databases, including data modelling and query optimization

• Strong backend engineering skills in at least one of: Python, TypeScript/Node.js, Java, Go or Scala. The squad works primarily in TypeScript and Python

• Production experience on AWS or GCP (we run on AWS), with containerized deployments (Docker, Kubernetes)

• Ability to design pipelines with traceability, audit trails and pseudonymisation in mind — knowing what was processed, when, and by which version of the transformation. Whether you learned this in a regulated industry or elsewhere does not matter to us

Production and operations

• Experience taking a data platform to production and operating it over time: deployment, monitoring, alerting, incident management

• Experience with observability tooling (Prometheus, Grafana, Datadog or equivalent) and with defining alerting on data pipelines

• At least one experience in a micro-services architecture

• Familiar with production development workflow (code reviews, branching models) and testing practices

• Good documentation skills

Soft Skills

• Fluency in both English (essential for team collaboration) and French (for local interaction) is required

• Curiosity and AI usage: We actively embrace working with AI productivity tools such as Claude to solve problems, sharpen code quality, and maximize efficiency. Fully leveraging AI in our daily work is not just encouraged — it's an essential strength we cultivate

• You enjoy working in a fast-paced and ever-changing environment

• Strong work ethic & daily act with integrity, honesty and fairness

• Definitely a thoughtful team player, looking to make your colleagues successful

Nice to have

• Experience driving technical decisions within a team: evaluating options, benchmarking, and documenting trade-offs

• Experience with large data volumes (Spark, Iceberg, lakehouse architectures)

• Knowledge of Avro, Parquet or Protobuf

• Already practiced TDD

• Open source project development experience

• Prior experience in a regulated environment (health data, finance, public sector), where traceability and audit trails are mandatory

A Note on Applying: We are looking for an experienced data engineer, but 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) – 30-45 min - Remote

2. 🧠 Technical Test with Michaël and Max - 1h30-2h - On-site

3. 🤖 Fit Interview with Louay (CTO) - 1 hour - On-site or Remote

4. 🤝 Meet the Team – 1 hour - On-site or Remote

5. 📞 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 (full-time), you have a base salary depending on your experience between 65k€ and 73k€

• 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 (progressively)

• Location: 29 rue du Louvre, 75002, PARIS