Cloud Data Engineer
hace 1 semana
**About Hakkoda**
We are a modern data consultancy empowering organizations to make informed decisions through data-driven insights.
We specialize in helping companies unlock the full potential of the Snowflake Data Cloud, providing consulting and managed services in data architecture, engineering, analytics, and science.
Our team is renowned for bringing expertise, ease of collaboration, and a fun culture that makes us a great place to work.
We are looking for curious and creative individuals who want to be part of a fast-paced, dynamic environment where everyone's input and efforts are valued.
As a Cloud Data Engineer, you will work on client engagements and Hakkoda teams in the US and Costa Rica.
You'll work directly with clients remotely, taking ownership of various work streams and their end products.
You will have the opportunity to build upon your proven engineering skills and leverage your interest in inspiring others, building strong relationships, and creating a true followership.
You'd be joining a team of passionate, forward-thinking engineers and data scientists charting a new course.
In a collaborative team setting, you'll work closely with others but also operate autonomously with little direction.
Your superior problem-solving, analytical, quantitative, and conceptual thinking skills, along with strong interpersonal and communication skills, will ensure successful client projects and team performance.
You will find a culture rich in collaboration, personal development, and one that recognizes and pursues the zest for life.
**Required Skills and Qualifications**:
- Bachelor's degree in Computer Science, Engineering, or other relevant fields.
- 2 - 4 years of experience as a DevOps engineer.
- Creating and deploying ML models in production on AWS, Azure, GCP.
- Proficiency in Kubernetes, microservices, Docker, Terraform, and Linux.
- Proficiency in programming languages such as Python, Golang, JavaScript, and others.
- Experience in Infrastructure as Code (IaC) languages like Terraform, Ansible, and others.
- Experience in CI/CD tooling like CircleCI, Jenkins, GitHub, and others.
- Experience in API lifecycle management.
**Responsibilities**:
- Networking experience with load balancing, network security, network protocols.
- Creating and deploying ML models in production on AWS, Azure, GCP.
- In charge of containerizing MLOps using Kubernetes.
- Generating ML offerings from a data catalog.
- Lead mid/associate level engineers throughout projects.
- Govern and orchestrate deployment of ML models in production.
- Configure microservices for data science workloads.
- Work with senior and lead-level DevOps, MLOps Engineers, and Data Scientists.
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