DataOps /​ MLOps Engineer - Strong DevOps Focus

About the Role

We are excited to announce an opportunity for a DataOps / MLOps Engineer remote position at CXG! As a growing global business with a presence in over 70 countries, we are looking for a talented individual to join our team and help us design and operate highly reliable, secure, and scalable DataOps and MLOps platforms.

What You'll Do

• Design, build, and operate DataOps and MLOps platforms with a strong engineering focus.
• Own the infrastructure, data, and ML production pipelines end-to-end, enforcing automation, testing, governance, and operational best practices.
• Act as the quality and reliability gatekeeper for all data and AI workloads.
• Utilize Infrastructure as Code (Terraform and related tools) to manage infrastructure efficiently.
• Implement CI/CD for data and ML pipelines, including testing, validation, and versioning.
• Manage workflow orchestration and scheduling using tools like Airflow.
• Oversee containerization and orchestration with Docker and Kubernetes (AKS).
• Manage cloud platform operations, focusing on AKS and supporting services.
• Govern and manage access across the data and AI ecosystem, including Snowflake access and roles.
• Integrate and manage Active Directory (AD) groups and identity-based access.
• Monitor, log, and ensure observability for data and ML systems.
• Maintain security, compliance, documentation, and standardization across all operations.

Requirements

• Deep expertise in DataOps and MLOps principles.
• Strong DevOps skills with a rigorous, engineering-first mindset.
• Experience with Infrastructure as Code (Terraform).
• Familiarity with CI/CD practices for data and ML pipelines.
• Proficient in workflow orchestration tools like Airflow.
• Experience with containerization technologies such as Docker and Kubernetes.
• Knowledge of cloud platforms, particularly AKS.
• Detail-oriented, methodical, and highly rigorous approach to engineering and operations.

Nice to Have

• Experience with Snowflake and dbt.
• Familiarity with ML lifecycle management.
• Understanding of monitoring, logging, and observability tools.

What We Offer

• Competitive salary range of $120,000 - $150,000 per year.
• Fully remote work environment with flexible hours.
• Opportunity to work with a diverse team across the globe.
• Professional development and growth opportunities.
• Engaging work culture focused on innovation and excellence.