Data Reliability Engineer

Job not on LinkedIn

🔥 19 hours ago

🇫🇷 France – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

⛑ DevOps & Site Reliability Engineer (SRE)

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Resilience

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2020

🏭 Manufacturing

🏥 Healthcare

📦 Logistics

Manufacturing • Healthcare • Logistics

Resilience is a leading biomanufacturing innovation company focused on the development of novel medicines. Specializing in the manufacturing of complex medicines such as cell and gene therapies, Resilience partners with small and mid-sized biotech firms to provide customized solutions that leverage cutting-edge technologies and scientific advancement. Their approach includes high-tech, end-to-end drug substance and drug product manufacturing capabilities aimed at ensuring rapid, safe, and scalable production. Resilience operates primarily in North America, with expertise in delivering regulatory-compliant solutions across global markets, enhancing the reliability and accessibility of biopharmaceutical supply chains.

📋 Description

• Build and operate data pipelines for ingestion from application events and databases, transformation, and export • Build pipeline tooling with SRE, including infrastructure as code, deployment, CI/CD, secrets management, database operations, and incident response • Monitor data quality and pipeline health using Grafana dashboards, alerting, metrics, and logs • Define and enforce data contracts and automated data-quality tests for freshness, completeness, and referential integrity • Deliver secure data exports to external partners and institutions • Provision and maintain dedicated PostgreSQL Research Spaces with study-specific access control and data scoping • Industrialize dbt projects so Data Analyst models are centralized, parallelized, and applied across multiple targets • Scope requests, assess feasibility, deliver solutions, and document them • Collaborate with product squads on emitted data and contribute to TypeScript implementation when needed • Participate in code reviews, technical design, and continuous improvement of engineering standards • Own the end-to-end data platform covering ingestion, transformation, exports, and underlying infrastructure • Support clinical research, medical, and operational stakeholders • Participate in screening, manager-fit, technical case study, team-fit, culture-fit, and strategic-fit hiring interviews

🎯 Requirements

• Production-grade Python, including tests, typing, code quality, reviews, and CI • Experience building and operating data pipelines and orchestration using Prefect, Airflow, Dagster, or equivalent • Experience with Kafka, S3, and SFTP • Advanced PostgreSQL SQL, including indexing, query plans, and incremental loads • Advanced dbt, including macros and Jinja, multi-target projects, incremental strategies, tests, packages, and CI integration • Terraform, Helm/Kubernetes, containers, CI/CD, monitoring, and alerting • Grafana or equivalent observability tooling • Ability to read and contribute to TypeScript codebases • Understanding of back-end API architecture, including REST design, versioning, authentication, pagination, and contracts • Strong communication skills • Ability to translate operational or scientific needs into technical specifications and assess feasibility/compliance • Comfort collaborating with SRE and scientific profiles on clinical trial data • Rigor with sensitive patient data • Ownership, autonomy, accountability, structured and detail-oriented approach, automation focus, and maintainability focus • Curiosity and continuous-learning mindset • Approximately 4–6 years in data engineering, platform engineering, or backend with a strong infrastructure component • Experience operating production pipelines with accountability for them • Experience writing and reviewing infrastructure as code in a team setting • Experience delivering data to stakeholders outside one's own team • Experience working in a maintained codebase with Git workflow, pull requests, and CI • Experience in contexts with high standards for security, compliance, or sensitive data • Healthcare data, GDPR-heavy, or HDS-hosted environment experience is a plus • Experience supporting scientific or clinical research users is a plus • Experience handling contractual data exchanges with external partners is a plus • Required English level selection from A1 to C2 in the application form

🏖️ Benefits

• Remote-friendly setup • Practical AI usage • Culture focused on automation, observability and continuous improvement • Direct contact with clinical research teams and operational stakeholders • Full ownership of data platform and infrastructure • Continuous-learning environment • No specific monetary benefits, insurance, retirement plan, paid leave, equity, or bonus stated