Analytics Software Engineer – Data Platform & AI

Resilience

France

Remote

EUR 65,000 - 95,000

Full time

14 days+

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Job summary

Resilience is seeking an Analytics Engineer to help build and scale our data foundations. You will own backend features for the Research Data Platform (Python/FastAPI, PostgreSQL) and maintain dbt models for reliable self-service analytics.

You’ll collaborate with researchers, clinicians and business teams to deliver timely insights and robust data tooling. You will work with a small team in a hybrid setup, using AI responsibly to drive automation while maintaining strong engineering ownership

Qualifications

  • Ship production-grade Python (tests, code quality, reviews, CI).
  • Build and maintain backend APIs (FastAPI/Flask/Django or equivalent).
  • Data modeling with advanced SQL to deliver production dbt models.
  • Use AI tools as a multiplier while keeping strong engineering ownership.
  • Deploy and operate what you build (containers, environments, CI/CD).
  • Implement data tests/alerting and troubleshoot data quality issues.

Responsibilities

  • Collaborate with Research/Clinical/Business users to iterate quickly and deliver value.
  • Participate in code reviews, technical design, and engineering standards improvements.
  • Support BI efforts with dashboards and business analysis.
  • Contribute to metrics governance via a semantic layer (Cube.js).
  • Turn recurring manual reporting into reliable tooling with automation.

Skills

Python
Backend APIs
SQL modeling
AI tools
CI/CD
Data tests

Tools

FastAPI
PostgreSQL
dbt
Cube.js

Job description

Resilience is seeking an Analytics Engineer to help build and scale our data foundations. You will own backend features for the Research Data Platform (Python/FastAPI, PostgreSQL) and maintain dbt models for reliable self-service analytics.

You’ll collaborate with researchers, clinicians and business teams to deliver timely insights and robust data tooling. You will work with a small team in a hybrid setup, using AI responsibly to drive automation while maintaining strong engineering ownership

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