Data Ops Engineer(x/f/m)

As a Data Ops Engineer at Doctolib, you’ll be responsible for designing, implementing, and maintaining our data infrastructure, ensuring smooth data flow and enabling data-driven decisions. Your role involves building robust pipelines, collaborating with data teams, automating workflows, and monitoring performance to guarantee data quality.

To qualify for the Data Ops Engineer position at Doctolib, applicants should have over two years of experience in similar roles, strong proficiency in data engineering tools, coding skills in languages like Python, and familiarity with cloud infrastructure and security best practices. Communication skills are also essential.

Data Ops Engineers at Doctolib should be proficient in programming languages like Python, which is essential for building and maintaining data pipelines. Knowledge of additional languages or frameworks, especially those used for API design, is considered a bonus.

Doctolib Data Ops Engineers utilize various tools for data engineering and infrastructure, including data warehouse solutions like Redshift or BigQuery, Docker for containerization, and orchestration tools like Airflow. Familiarity with infrastructure-as-code tools like Terraform is also advantageous.

Collaboration at Doctolib is vital as Data Ops Engineers regularly engage with data scientists, engineers, and business teams to gather requirements and ensure that the data infrastructure meets organizational needs. This interaction fosters a dynamic and innovative working environment.

Doctolib offers an array of benefits for Data Ops Engineers, including free health insurance, parental care programs, flexible working options, and well-being initiatives. There’s also support for professional development and opportunities for career advancement within a collaborative team.

The work culture at Doctolib for Data Ops Engineers is collaborative and inclusive, emphasizing diversity and respect. The team is passionate about making a difference in healthcare and values contributions from all employees, creating a dynamic and supportive workplace.

When answering this question, elaborate on projects where you've designed data infrastructures. Highlight specific tools and technologies you've used, your approach to scalability and security, and any challenges you faced while implementing those designs.

Discuss methodologies for ensuring the reliability and efficiency of data pipelines. Include practices like regular monitoring, automated testing, and documentation that help identify bottlenecks and resolve issues quickly.

Explain how you’ve integrated automation in your previous roles, focusing on tools and methods you've used. Discuss how automation has improved efficiency and reduced manual errors in your data processes.

Share a specific example where you identified a data quality problem, your role in resolving it, and the steps you took to ensure better data management in the future. Highlight the importance of data accuracy and reliability.

Mention specific experiences with cloud services like AWS, Azure, or GCP. Elaborate on how you've leveraged these platforms' capabilities, relating them to data pipeline construction or performance optimization.

Discuss your understanding of data governance principles and best practices for securing data. Emphasize the importance of compliance and your proactive measures in implementing security protocols.

Provide insights into how you've implemented CI/CD pipelines for data operations. Explain the tools you used and how they helped streamline your data deployment process for quicker and safer updates.

Describe a situation where you managed conflicting demands from different stakeholders. Explain your approach to prioritizing tasks, facilitating discussions, and achieving a resolution that satisfies everyone involved.

Discuss your approach to cost optimization by analyzing resource utilization and identifying unnecessary expenditure. Highlight any tools or techniques you've used to monitor and reduce costs effectively.

Share your personal motivations for wanting to join Doctolib. Discuss your alignment with the company’s mission in healthcare and how you see yourself contributing to their goals through your skills in data infrastructure and collaboration.