It's great that you're thinking about your career progression! With your background as a Cloud Support Engineer, ETL tester, and QE, combined with your CS Engineering degree and MS in Software Engineering (specialized in Cloud/Data Science), you have a strong foundation for several high-paying roles. Here are some options you can consider, along with the skills you might need to focus on:

**1. Cloud Solutions Architect:**

* **What they do:** Design and implement cloud computing solutions for organizations. This involves understanding business needs, designing cloud infrastructure, and ensuring security and scalability.
* **Why it's a good fit:** Your experience in cloud support gives you practical knowledge of cloud environments, while your MS in Software Engineering provides the theoretical background.
* **Skills to develop:** Cloud architecture patterns, cloud security, cost optimization, and strong communication skills to interact with clients.
* **Potential Salary:** Very high, often exceeding $150,000 per year.

**2. Cloud DevOps Engineer:**

* **What they do:** Bridge the gap between software development and IT operations, automating processes and ensuring smooth deployment and operation of cloud-based applications.
* **Why it's a good fit:** Your experience in testing (ETL and QE) gives you a good understanding of the software development lifecycle, which is crucial for DevOps.
* **Skills to develop:** CI/CD (Continuous Integration/Continuous Deployment) pipelines, infrastructure as code (IaC), containerization (Docker, Kubernetes), and automation tools.
* **Potential Salary:** Also very high, often in the $120,000-$150,000 range.

**3. Cloud Security Engineer:**

* **What they do:** Focus on securing cloud environments, protecting data and infrastructure from threats.
* **Why it's a good fit:** With increasing concerns about data breaches, this is a high-demand area. Your experience in testing can be valuable in identifying vulnerabilities.
* **Skills to develop:** Cloud security best practices, security tools and technologies, compliance standards, and ethical hacking.
* **Potential Salary:** Highly competitive, similar to Cloud Solutions Architect.

**4. Cloud Data Engineer:**

* **What they do:** Build and maintain data pipelines and infrastructure in the cloud, enabling data storage, processing, and analysis.
* **Why it's a good fit:** Your MS specialization in Data Science, combined with your ETL testing experience, makes this a natural progression.
* **Skills to develop:** Big data technologies (Hadoop, Spark), data warehousing, ETL processes, and cloud-based data services.
* **Potential Salary:** Very attractive, often in the $120,000-$150,000 range.

**5. Data Scientist/Machine Learning Engineer (with Cloud Focus):**

* **What they do:** Apply statistical and machine learning techniques to analyze data and build predictive models, often leveraging cloud resources for scalability.
* **Why it's a good fit:** Your MS specialization in Data Science is directly relevant here.
* **Skills to develop:** Machine learning algorithms, statistical modeling, programming languages (Python, R), and cloud-based machine learning platforms.
* **Potential Salary:** Can be very high, especially with experience and a strong portfolio.

**Key Considerations:**

* **Certifications:** Obtaining relevant cloud certifications (AWS, Azure, GCP) can significantly boost your career prospects.
* **Networking:** Attend industry events and connect with people in your desired field.
* **Projects:** Work on personal projects to showcase your skills and experience.

By focusing on developing the relevant skills and gaining practical experience in your chosen area, you can position yourself for a high-paying and fulfilling career in the cloud computing industry.

with your background as a cloud support engineer, along with experience as an etl tester and quality engineer, you have access to several high-paying career opportunities in the tech industry. below is an overview of potential roles you might explore, along with their average salaries and required skills.

potential high-paying roles

1. cloud solutions architect
- average salary: ₹25-30 lakhs per year
- role: design and oversee cloud-based solutions that align with business objectives and technical needs.
- requirements: expertise in cloud platforms such as aws, azure, or google cloud, along with strong architecture design capabilities.

2. cloud data scientist
- average salary: ₹22-28 lakhs per year
- role: analyze and handle large datasets within cloud environments, often leveraging machine learning techniques.
- requirements: proficiency in tools and languages like python or r, as well as strong analytical skills.

3. cloud devops engineer
- average salary: ₹20-26 lakhs per year
- role: automate and optimize software development processes within cloud platforms.
- requirements: familiarity with ci/cd tools, scripting languages, and cloud infrastructure.

4. cloud security engineer
- average salary: ₹20-25 lakhs per year
- role: secure cloud environments and data by implementing robust security measures and ensuring compliance.
- requirements: understanding of security frameworks and certifications like aws certified security specialty.

5. senior cloud support engineer
- average salary: ₹26-32 lakhs per year
- role: provide expert-level support for cloud services, often managing teams or projects.
- requirements: extensive experience in cloud technologies and customer support processes.

6. cloud automation engineer
- average salary: ₹22-30 lakhs per year
- role: create automation tools to enhance operational efficiency within cloud systems.
- requirements: knowledge of automation frameworks and relevant programming skills.

key skills to develop

to transition into these roles successfully, focus on strengthening the following skills:

- cloud platforms: gain in-depth knowledge of leading platforms like aws, azure, and google cloud.
- programming: build proficiency in languages such as python, java, or go.
- data tools: learn to work with big data processing tools like hadoop and spark.
- devops: master ci/cd pipelines, containerization using docker, and orchestration with kubernetes.

summary

your current role and prior experience position you well for high-demand roles like cloud solutions architect or cloud data scientist. these paths align with your expertise while offering significant growth potential. to make this transition, prioritize certifications and practical experience in cloud technologies.

sources:
1. https://6figr.com/in/salary/cloud-support-engineer--t
2. https://www.techtarget.com/whatis/feature/Top-7-cloud-computing-careers-and-how-to-get-started
3. https://informatica.gr8people.com/jobs?page=1&SID=10526&cext=infasocial-emp&location=Bengaluru,+KA&jobCategory=4
4. https://in.indeed.com/q-cloud-support-engineer-jobs.html