DataCouch is a leading training company that specialises in providing high-quality courses and training programs in various technical fields. Our academy is dedicated to equipping students and professionals with the latest skills and knowledge in areas such as AI/ML Cloud DevOps Data and other cutting-edge technologies. We are committed to delivering exceptional learning experiences and helping individuals thrive in their careers. We are looking for a DevOps Engineer to manage infrastructure automate deployment processes and ensure smooth and reliable system operations.
Requirements
Key Responsibilities
Manage CI/CD pipelines and deployment processes
Handle cloud infrastructure (AWS / Azure / GCP)
Monitor system performance and ensure uptime
Automate workflows and improve system efficiency
Collaborate with development teams for releases
Skills & Requirements
Knowledge of Linux Git and scripting (Bash/Python)
Experience with CI/CD tools (Jenkins GitHub Actions etc.)
Problem-solving and troubleshooting skills
Understanding of cloud platforms and containerization (Docker Kubernetes)
Benefits
Learn directly from industry experts who value creativity and curiosity. Get space to explore experiment and grow your skills. Work in a culture where tech meets creativity and new ideas always have a voice. If youve been waiting for a place to prove your creative spark DataCouch is that place.
Required Skills:
Educational Background: Bachelors and Masters degrees in Data Science Computer Science Statistics or a related field. Technical Skills: Proficient in Python and familiar with key data science libraries (Pandas Scikit-Learn TensorFlow or PyTorch). Strong understanding of all complex machine learning algorithms not limited to decision trees random forests and gradient boosting machines. Competence in data preprocessing cleaning and analysis. Familiarity with data cleaning transformation and preprocessing techniques. Experience with SQL and possibly some NoSQL databases for data querying and manipulation. Basic knowledge of data visualization tools like Matplotlib and Seaborn. Strong skills in SQL for data extraction and the ability to work with complex database systems. Advanced knowledge of analytical tools and software such as Excel Tableau or more specialized software depending on the industry (e.g. SAS SPSS). Experience with data visualization and the ability to create interactive dashboards. Vast knowledge of NLP Deep Learning Machine Learning Knowledge of genAI with implementation knowledge (LLM fine tuning RAG implementation) and many more. Familiarity with cloud services (AWS Azure Google Cloud) for data processing and storage.. Professional Experience: 2-3 years of experience in a data science or related role. Proven track record of developing and deploying machine learning models to solve business problems. Experience in projects that involve complex data structures and large-scale datasets. Exposure to model validation and implementation in a production environment. Demonstrated experience in analyzing large datasets and delivering actionable insights. Proven track record of effectively communicating findings to help inform business decisions. Experience in performing statistical analysis forecasting and establishing data structures that optimize analytical capabilities. Soft Skills: Strong problem-solving skills with a capability to work through complex issues using a logical and analytical approach. Good communication skills to effectively articulate insights and technical details to non-technical stakeholders. Ability to work collaboratively in team settings and manage project timelines effectively. Strong attention to detail with the capability to work on multiple projects simultaneously. Effective communication skills capable of presenting complex information in an understandable and compelling manner. Collaboration skills to work effectively with both technical teams and business units.
DataCouch is a leading training company that specialises in providing high-quality courses and training programs in various technical fields. Our academy is dedicated to equipping students and professionals with the latest skills and knowledge in areas such as AI/ML Cloud DevOpsData and other cuttin...
DataCouch is a leading training company that specialises in providing high-quality courses and training programs in various technical fields. Our academy is dedicated to equipping students and professionals with the latest skills and knowledge in areas such as AI/ML Cloud DevOps Data and other cutting-edge technologies. We are committed to delivering exceptional learning experiences and helping individuals thrive in their careers. We are looking for a DevOps Engineer to manage infrastructure automate deployment processes and ensure smooth and reliable system operations.
Requirements
Key Responsibilities
Manage CI/CD pipelines and deployment processes
Handle cloud infrastructure (AWS / Azure / GCP)
Monitor system performance and ensure uptime
Automate workflows and improve system efficiency
Collaborate with development teams for releases
Skills & Requirements
Knowledge of Linux Git and scripting (Bash/Python)
Experience with CI/CD tools (Jenkins GitHub Actions etc.)
Problem-solving and troubleshooting skills
Understanding of cloud platforms and containerization (Docker Kubernetes)
Benefits
Learn directly from industry experts who value creativity and curiosity. Get space to explore experiment and grow your skills. Work in a culture where tech meets creativity and new ideas always have a voice. If youve been waiting for a place to prove your creative spark DataCouch is that place.
Required Skills:
Educational Background: Bachelors and Masters degrees in Data Science Computer Science Statistics or a related field. Technical Skills: Proficient in Python and familiar with key data science libraries (Pandas Scikit-Learn TensorFlow or PyTorch). Strong understanding of all complex machine learning algorithms not limited to decision trees random forests and gradient boosting machines. Competence in data preprocessing cleaning and analysis. Familiarity with data cleaning transformation and preprocessing techniques. Experience with SQL and possibly some NoSQL databases for data querying and manipulation. Basic knowledge of data visualization tools like Matplotlib and Seaborn. Strong skills in SQL for data extraction and the ability to work with complex database systems. Advanced knowledge of analytical tools and software such as Excel Tableau or more specialized software depending on the industry (e.g. SAS SPSS). Experience with data visualization and the ability to create interactive dashboards. Vast knowledge of NLP Deep Learning Machine Learning Knowledge of genAI with implementation knowledge (LLM fine tuning RAG implementation) and many more. Familiarity with cloud services (AWS Azure Google Cloud) for data processing and storage.. Professional Experience: 2-3 years of experience in a data science or related role. Proven track record of developing and deploying machine learning models to solve business problems. Experience in projects that involve complex data structures and large-scale datasets. Exposure to model validation and implementation in a production environment. Demonstrated experience in analyzing large datasets and delivering actionable insights. Proven track record of effectively communicating findings to help inform business decisions. Experience in performing statistical analysis forecasting and establishing data structures that optimize analytical capabilities. Soft Skills: Strong problem-solving skills with a capability to work through complex issues using a logical and analytical approach. Good communication skills to effectively articulate insights and technical details to non-technical stakeholders. Ability to work collaboratively in team settings and manage project timelines effectively. Strong attention to detail with the capability to work on multiple projects simultaneously. Effective communication skills capable of presenting complex information in an understandable and compelling manner. Collaboration skills to work effectively with both technical teams and business units.
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