Data Ops Engineer

My client is one of the largest Mining & Metals companies globally.

The Senior DevOps Engineer will play a critical role in building, scaling, automating, and maintaining the company’s Big Data infrastructure and Machine Learning operations (MLOps). This individual will work in close collaboration with our Data Architect, Data Science, Data Engineering, and IT teams to ensure the development, deployment and scale of robust, high-performance data processing systems and ML models.

Responsibilities:

• Big Data Infrastructure: Design, build, and maintain high-performance, cloud[1]based, fault-tolerant, scalable distributed Data infrastructure that supports the company’s data-intensive applications. (Real time/Batch/LLM’s). This includes developing strategies for data storage (TB’s), processing, and analysis, and implementing high-performance, scalable data pipelines for ML models and data products, supporting up to 50-60 usecases a year and thousands of IoT devices.
• Create infrastructure as Code, perform configuration and set up managed data services. Build and deploy a data science playground for research and prototyping for the professional and citizen data science program being rolled out and supporting 15-20 citizen data scientists/ ambassadors.
• Machine Learning Operations (MLOps): Develop and manage the ML operational process, working closely with the data science team to implement ML models into production Including edge. This includes streamlining the ML lifecycle, from model development and testing to deployment and implementing the monitoring and alerting strategy.

Qualifications & Experience:

• Bachelor’s in Data Science, Computer Science, Engineering, Statistics
• 10+ years of relevant experience.
• A minimum of 5-7 years of experience in a DevOps role, with a focus on managing Big Data infrastructures and MLOps.

Technical Skills:

• Strong experience with Big Data technologies such as Hadoop, Spark, Kafka, etc.
• Proven expertise in managing and deploying ML models into production.
• Proficient in using CI/CD tools like Jenkins, Travis CI, CircleCI, etc.
• Proficient in using infrastructure automation tools like Terraform, Chef, Puppet, Ansible, etc.
• Strong knowledge of cloud platforms such as Azure (AWS, GCP)

*** Only successful candidates will be contacted ***

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