DataOps Engineer

Role Overview
 

Beyond the strong technical skills, we’re looking for someone who enjoys being part of a team while also being comfortable working independently. The ideal candidate is proactive, takes ownership of their work, and is naturally curious: someone who enjoys learning, improving, and staying engaged with what they do. We value people who are genuinely interested in their work and motivated to contribute, not just execute tasks.
 

- Design, build and maintain scalable ETL/ELT pipelines and data models in Snowflake.
 

- Ensure data is reliable, high-quality, and performs well across different workflows
 

- Monitor pipelines, troubleshoot issues and continuously improve performance
 

- Work closely with data analysts, BI developers and other stakeholders to understand and support business needs
 

- Take ownership of deploying and operating data pipelines, including CI/CD processes and releases.
 

- Have strong practical experience with AWS
 

- Comfortable working with Git and modern development workflows
 

- Familiarity with cloud infrastructure and tools such as Terraform or Docker
 

- Own the stability and performance of data workflows in production environments
 

- Contribute to automation, as well as monitoring, logging and alerting for data workflows.
 

- Support environment management and ensure smooth operation of data pipelines in production
 

- Bring strong hands-on experience with Snowflake.
 

- Experience working in a data engineering team, building data warehouses and pipelines. 
 

- Pharma domain experience: nice to have.