Senior DataOps Engineer

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Requirements:

• 5+ years of experience in DataOps, data engineering, or a similar role, preferably in a regulated industry.
• Exceptional Python programming skills focused on automation.
• Proficiency with SQL and NoSQL databases and experience in designing complex data pipelines.
• Expertise in cloud platforms (AWS, GCP, Azure) and tools like Terraform, Kubernetes, and Docker.
• Advanced understanding of data security and compliance, especially GDPR or ISO standards.
• Proven ability to work autonomously and deliver measurable results.
• Strong communication and leadership skills.
• Fluency in English.

Responsibilities:

• Lead the Design and Implementation: Architect and maintain high-performance, secure, and scalable data pipelines for AI-driven clinical workflows.
• Drive Integration: Collaborate with teams to manage the ingestion, transformation, and integration of large datasets.
• Enhance Data Quality and Compliance: Build systems to ensure data quality and regulatory compliance.
• Build and Automate: Develop reusable code and frameworks in Python to streamline data processes.
• Monitor and Troubleshoot: Proactively monitor data pipelines, resolve issues, and implement safeguards.
• Innovate: Identify and implement best practices and emerging technologies.
• Collaborate Globally: Serve as a technical expert, ensuring alignment on project goals.