Data Engineer

About us

Implicity is a digital MedTech that brings innovations to cardiologists, using Big Data and Artificial Intelligence. It offers a remote monitoring platform that simplifies data management and enables better care and prevention for patients. Founded in 2016, Implicity serves over 250 hospitals and medical centers, covering more than 100,000 patients. The team includes experts in data science, engineering, clinical, regulatory, IT, sales, and customer success, and it is a leading player in European cardiology, expanding into the US market.

Job and recruitment context

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

Responsibilities

• 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.

Technical Environment

• Languages: Python, Java, TypeScript
• Data Processing: Spark (Glue), Apache Beam (or Flink)
• Storage & Table Format: PostgreSQL, Apache Iceberg, S3
• Integration & Messaging: RabbitMQ
• Infrastructure & DevOps: AWS, Terraform, Docker, Kubernetes, GitLab CI
• Analytics & OLAP Systems: DBT, Cube, Metabase, Athena
• Methodology: Agile (Scrum), Lean management

Profile and Mindset

• Intermediate level with 3 to 5 years of hands‑on experience in data engineering.
• Education: Master or Engineer in Computer Science, Engineering, or related field.
• Languages: Fluent in English and French.
• Core Engineering: Solid SQL and modeling skills; hands‑on experience with Python or Java.
• Cloud Platform: Experience with AWS, GCP, or Azure is required.
• Data Processing: Proven experience building robust ETL/ELT pipelines at GB/TB scale with batch or streaming frameworks (Spark, Beam, Flink, Hadoop) and automated quality checks.
• Orchestration: Experience with Dagster or Airflow is required.
• Lakehouse or Data Warehouse: Experience with Snowflake, BigQuery, or Apache Iceberg/S3 is a plus.
• Engineering Standards: Ability to apply best practices to build maintainable pipelines while balancing technical debt.
• AI tools: Prefer engineers who use AI‑assisted tools (Cursor, Claude, Copilot).
• Health & Privacy: Interest in healthcare data and familiarity with GDPR/HDS; prior exposure to FHIR is a plus.
• Soft Skills: Pragmatic, focused, autonomous, self‑driven, curious, and adaptable.

Recruitment Process

1. 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 – 1 hour 30 minutes (On‑site).
4. Fit Interview with the CTO – 1 hour (On‑site or remote) – Focus on fit and culture.
5. Meet the Team – 30 minutes (Optional).
6. Reference Check & Offer – usually follows within 72 hours.

Benefits

• Benefits Health care plan: Alan (50% employer).
• Luncheon voucher: 9€ (50% employer).
• Transport: 50% of your pass or sustainable mobility pass.
• Remote work: 3 days per week.

Salary

Base salary between €55,000 and €60,000 depending on experience, plus eligible stock options (BSPCEs) as per company rules.

Remote work & Location

Remote work with three days per week onsite at 29 rue du Louvre, 75002 Paris.