30 Cloud Platforms jobs in Noida

• Design, build, and maintain scalable data pipelines on cloud platforms (AWS, Azure, GCP).
• Develop and optimize ETL/ELT processes for large-scale data ingestion and transformation.
• Create and manage data models to support business intelligence and machine learning applications.
• Implement data warehousing solutions and data lakes.
• Ensure data quality, integrity, and security across all data systems.
• Collaborate with data scientists and analysts to define data requirements and provide data solutions.
• Write efficient and maintainable code in SQL, Python, or other relevant languages.
• Optimize data processing performance and storage efficiency.
• Develop and implement data governance policies and procedures.
• Troubleshoot and resolve complex data-related issues.
• Contribute to the development of CI/CD pipelines for data infrastructure.

• Bachelor's or Master's degree in Computer Science, Engineering, or a related quantitative field.
• Proven experience as a Data Engineer, with a strong focus on cloud platforms (AWS, Azure, GCP).
• Proficiency in SQL, Python, and big data technologies (e.g., Spark, Hadoop).
• Experience with data warehousing solutions (e.g., Snowflake, Redshift, BigQuery).
• Strong understanding of ETL/ELT concepts and tools.
• Familiarity with data modeling techniques and best practices.
• Experience with containerization technologies (e.g., Docker, Kubernetes) is a plus.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills for remote teamwork.

• Lead the design, development, and deployment of AI/ML models and applications on cloud platforms.
• Architect scalable and robust machine learning pipelines and infrastructure.
• Manage and mentor a team of AI/ML engineers, fostering a collaborative environment.
• Implement MLOps best practices for continuous integration, deployment, and monitoring.
• Conduct research and experiments to evaluate and select appropriate ML algorithms and frameworks.
• Collaborate with cross-functional teams to define project requirements and deliverables.
• Optimize model performance, scalability, and efficiency.
• Ensure the security and ethical considerations of AI/ML solutions.
• Stay abreast of the latest advancements in AI, ML, and cloud technologies.
• Present findings and technical roadmaps to stakeholders.

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Minimum of 7-10 years of experience in AI/ML engineering, with at least 3 years in a leadership role.
• Extensive experience with cloud platforms (AWS, Azure, GCP) and their ML services.
• Proficiency in Python and ML libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong understanding of data structures, algorithms, and software design principles.
• Experience with MLOps tools and practices.
• Excellent leadership, communication, and interpersonal skills.
• Proven ability to manage and mentor engineering teams in a remote setting.
• Strong analytical and problem-solving skills.
• Experience with big data technologies is a plus.

• Architecting and developing scalable, production-ready machine learning models and algorithms, with a focus on deep learning, NLP, and computer vision.
• Designing and implementing robust MLOps pipelines for automated model training, deployment, monitoring, and versioning on cloud infrastructure (AWS, Azure, GCP).
• Leading the selection and evaluation of appropriate ML frameworks, tools, and technologies.
• Collaborating closely with product managers, data scientists, and software engineers to define ML requirements and translate them into technical solutions.
• Driving research and development into novel AI/ML techniques and their application to business problems.
• Mentoring and guiding junior engineers and data scientists within the team.
• Ensuring the performance, scalability, reliability, and security of deployed ML systems.
• Staying abreast of the latest research trends, publications, and industry best practices in AI/ML.
• Contributing to the technical roadmap and strategic direction of the AI/ML initiatives.
• Developing and maintaining comprehensive documentation for ML models, pipelines, and systems.

• Design, develop, and maintain full-stack web applications, with a focus on scalability and performance on cloud platforms.
• Write clean, efficient, and well-documented code for both front-end and back-end components.
• Collaborate with product managers, designers, and other engineers to translate requirements into technical solutions.
• Develop and manage APIs and microservices.
• Implement and manage CI/CD pipelines for automated testing and deployment.
• Optimize applications for maximum speed, scalability, and security in cloud environments (AWS, Azure, GCP).
• Troubleshoot, debug, and upgrade existing software.
• Participate in code reviews to ensure code quality and adherence to best practices.
• Stay updated with emerging technologies and industry trends in software development and cloud computing.
• Mentor junior engineers and contribute to technical discussions and decision-making.
• Ensure security best practices are implemented throughout the development lifecycle.

• Bachelor's degree in Computer Science, Engineering, or a related field. Master's degree preferred.
• Minimum of 7 years of professional software development experience.
• Proficiency in at least one modern front-end framework (e.g., React, Angular, Vue.js).
• Strong experience with back-end languages and frameworks (e.g., Node.js, Python/Django, Java/Spring, Ruby on Rails).
• Extensive experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Solid understanding of database technologies (SQL and NoSQL) and data modeling.
• Experience with containerization technologies (e.g., Docker, Kubernetes) is highly desirable.
• Familiarity with Agile development methodologies.
• Excellent problem-solving, analytical, and debugging skills.
• Strong communication and collaboration skills, with the ability to work effectively in a hybrid team environment.
• Experience with building and consuming RESTful APIs.

• Lead the design, development, and implementation of scalable and reliable microservices architectures on cloud platforms (e.g., AWS, Azure, GCP).
• Architect and build robust CI/CD pipelines to ensure efficient and automated software delivery.
• Write high-quality, maintainable, and testable code in languages such as Java, Python, Go, or Node.js.
• Mentor and guide a team of software engineers, fostering a culture of technical excellence and collaboration.
• Collaborate with product managers, architects, and other stakeholders to define technical requirements and roadmaps.
• Drive best practices in software development, including code reviews, unit testing, integration testing, and performance optimization.
• Troubleshoot and resolve complex technical issues in production environments.
• Contribute to the strategic direction of the engineering organization, evaluating new technologies and approaches.
• Ensure the security, scalability, and performance of cloud-based applications.
• Participate in on-call rotation for critical system support.

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 8+ years of professional experience in software development, with at least 3 years in a lead or senior technical role.
• Extensive experience designing and building distributed systems and microservices.
• Deep expertise in cloud computing platforms (AWS, Azure, or GCP) and containerization technologies (Docker, Kubernetes).
• Strong proficiency in at least one modern programming language (e.g., Java, Python, Go).
• Proven experience with CI/CD tools and practices (e.g., Jenkins, GitLab CI, CircleCI).
• Solid understanding of networking concepts, database technologies (SQL/NoSQL), and system security.
• Excellent problem-solving, analytical, and debugging skills.
• Strong leadership, communication, and mentoring capabilities.
• Experience with agile development methodologies.

GCP/Bigdata

Provides technical leadership in Big Data space (Hadoop Stack like Spark, M/R, HDFS, Hive, HBase etc) and contributes to open source Big Data technologies.

Must have : Operating knowledge of cloud computing platforms (GCP, especially Big Query, Dataflow, Dataproc, Storage, VMs, Networking, Pub Sub, Cloud Functions, Composer servics)

Should be aware with columnar database e.g parquet, ORC etc

Visualize and evangelize next generation infrastructure in Cloud platform/Big Data space (Batch, Near Real-time, Real-time technologies).

Passionate for continuous learning, experimenting, applying and contributing towards cutting edge open source technologies and software paradigms

Developing and implementing an overall organizational data strategy that is in line with business processes. The strategy includes data model designs, database development standards, implementation and management of data warehouses and data analytics systems

Expert-level proficiency in at-least 4-5 GCP services

Experience with technical solutions based on industry standards using GCP - IaaS, PaaS and SaaS capabilities

Strong understanding and experience in distributed computing frameworks, particularly

Experience working within a Linux computing environment, and use of command line tools including knowledge of shell/Python scripting for automating common task

KV Tech Solutions Pvt Ltd embodies the spirit of innovation and adaptability in today's rapidly evolving digital landscape. Our mission is to transform businesses with Google Cloud excellence. We are a team of experts dedicated to providing cutting-edge solutions in areas like VM migrations, Generative AI, data transformation, and predictive analytics. To learn more about our work, visit our website at

The Role: Google Cloud Specialist

We are seeking a highly motivated and experienced Google Cloud Specialist to join our team in a full-time, remote capacity. This role is ideal for a candidate who is ready to leverage their hands-on experience and Google Professional Certification to design, implement, and deploy cutting-edge cloud and data solutions for our clients.

Salary Range: 3.5 LPA to 4 LPA

Your Responsibilities

As a Google Cloud Specialist, you will be a key contributor to our client projects, applying your expertise across the Google Cloud ecosystem.

You will:

• Design and deploy robust full-stack applications using serverless technologies like Google Cloud Run or App Engine.
• Develop and implement scalable data pipelines for batch and streaming data, including deploying jobs to Dataproc to process and load data into BigQuery.
• Deploy, manage, and monitor Machine Learning (ML) models for online and batch predictions using Vertex AI Endpoints and Model Registry.
• Work on projects involving advanced areas like VM migrations, Generative AI, data transformation, and predictive analytics.
• Contribute to meaningful solutions for clients in industries such as Healthcare, Government, Retail, and Telecom.
• Design and deploy secure, well-architected cloud environments and application development/secure landing zones.
• Stay current with new Google Cloud features and services to recommend and implement optimal client solutions.

Required Skills & Qualifications

Please note: Only candidates meeting the following mandatory requirements will be considered for this role.

• Experience: 1 to 3 years of hands-on, verifiable experience working with Google Cloud technologies.
• Certification: Must possess a current, valid Google Professional Certification (e.g., Professional Cloud Architect, Professional Data Engineer, Professional Cloud Developer, etc.).

Candidates must possess a strong subset of the following technical skills:

• Demonstrable experience in deploying applications to serverless platforms like Cloud Run or App Engine.
• Practical experience in building and executing data processing jobs/pipelines using technologies like Dataproc, and data warehousing on BigQuery.
• Proficiency in the Vertex AI platform for model deployment, including creating a Model Registry entry and deploying to a managed Endpoint for online serving.
• Deep understanding of IT concepts, cloud computing principles, and the Google Cloud Platform (GCP) service portfolio.
• Excellent problem-solving skills, a proactive attitude, and the ability to work independently in a remote setting.

Interview & Application Requirements

To ensure candidates have practical, up-to-date skills, the interview process will include a hands-on demonstration:

• Pre-Interview Task: Interested candidates must be able to utilize their free Google Cloud trial account.
• Interview Demonstration: Be prepared to demo foundational knowledge and practical application of the following concepts:
• Google Cloud Foundation Fabric (Demonstrate your ability to establish core GCP networking, security, and resource hierarchy principles).
• Google Agentspace (Showcase your understanding or a basic demo of using Google's generative AI tools or services for a practical business application).

Added Advantage

• Familiarity with Infrastructure as Code (e.g., Terraform).
• Experience with Python (especially the Vertex AI SDK), Go, or other relevant programming languages for application, data pipeline, and ML development.
• Exposure to containerization and orchestration (e.g., Docker, Kubernetes, Artifact Registry).

To Apply

Please submit your resume and a cover letter detailing your 1-3 years of Google Cloud experience, the Google Professional Certification you hold (including the date of achievement), and your readiness to complete the required interview demo.

Overview of 66degrees

66degrees is a leading consulting and professional services company specialising in developing Al-focused, data-led solutions leveraging the latest advancements in cloud technology. With our unmatched engineering capabilities and vast industry experience, we help the world's leading brands transform their business challenges into opportunities and shape the future of work. At 66degrees, we believe in embracing the challenge and winning together. These values not only guide us in achieving our goals as a company but also for our people. We are dedicated to creating a significant impact for our employees by fostering a culture that sparks innovation and supports professional and personal growth along the way.

Role Overview

We are seeking a highly skilled and experienced Google Cloud and Workspace Engineer/Administrator to join our dynamic team. In this role, you will be responsible for the comprehensive management and administration of all Google products, projects, sandboxes, and related infrastructure within the Google Cloud Platform (GCP), alongside the administration of Google Workspace. You will play a crucial role in ensuring the stability, security, and optimal performance of our cloud and collaboration environments.

Key Responsibilities:

Google Cloud Platform Administration:

• Manage and administer Google Cloud projects, including creation, configuration, and resource allocation.
• Oversee the deployment, monitoring, and maintenance of various Google Cloud services (e.g., Compute Engine, Cloud Storage, Cloud SQL, BigQuery, Kubernetes Engine).
• Implement and enforce security best practices within GCP, including IAM, network security, and data encryption.
• Monitor cloud resource usage, identify cost optimization opportunities, and implement efficiency improvements.
• Troubleshoot and resolve cloud infrastructure issues in a timely manner.

Google Workspace Administration:

• Administer and support Google Workspace services, including Gmail, Drive, Calendar, Meet, and Chat.
• Manage user accounts, groups, organizational units, and access permissions within Google Workspace.
• Implement and enforce security and compliance policies for Google Workspace.
• Provide technical support and guidance to users on Google Workspace features and best practices.
• Monitor Google Workspace usage and identify opportunities for optimization.

Cloud adoption strategy:

• The ability to align the SLZ deployment with the larger Cloud Adoption Framework (CAF) and a clear business case for moving workloads to a sovereign cloud environment.
• Manage the overall setup and configuration of SLZ

Product and Sandbox Management:

• Administer and support various Google products and applications integrated with GCP and Google Workspace.
• Manage and maintain sandbox environments for development, testing, and experimentation.
• Ensure proper access control and resource allocation for sandbox users.

Automation and Scripting:

• Develop and implement automation scripts (e.g., Python, Bash, Terraform) for routine cloud and Workspace operations and infrastructure provisioning.
• Utilize Infrastructure as Code (IaC) principles to manage and deploy cloud resources.

Monitoring and Alerting:

• Set up and manage monitoring tools and dashboards for cloud infrastructure and applications, as well as Google Workspace.
• Configure alerts and notifications for critical events and performance thresholds.

Network Segmentation:

• Implement strong network segmentation using VPCs, subnets, and firewall rules to isolate different environments (e.g., production, development, staging) and workloads within the SLZ.

Identity and Access Management (IAM):

• Establish a robust IAM strategy with granular permissions, principle of least privilege, and multi-factor authentication (MFA) for all access to the SLZ, leveraging Google Cloud IAM roles and custom roles as needed.

Logging and Monitoring:

• Configure comprehensive logging and monitoring capabilities using Cloud Logging and Cloud Monitoring to capture all activities, security events, and resource utilization within the SLZ, enabling proactive threat detection and compliance auditing.

Security Services Integration:

• Integrate native Google Cloud security services such as Security Command Center, Cloud Armor, and Cloud IDS/IPS to enhance threat protection, vulnerability management, and real-time anomaly detection within the SLZ.

Documentation:

• Create and maintain comprehensive documentation for cloud and Workspace architecture, configurations, and operational procedures.

Collaboration:

• Collaborate with development, operations, and security teams to ensure seamless integration and support of cloud and collaboration solutions.
• Provide technical guidance and support to internal teams on GCP and Google Workspace best practices.

Qualifications:

• Bachelor's degree in Computer Science, Information Technology, or a related field, or equivalent practical experience.
• Proven experience as a Google Cloud Engineer/Administrator or similar role.
• Proven experience in administering Google Workspace.
• Proven experience in establishing, maintaining, and managing Google Cloud billing accounts, cloud spends and overall financials ensuring strict adherence to financial policies and regulatory requirements.
• In-depth knowledge of Google Cloud Platform services and architecture.
• Strong understanding of networking concepts (VPC, VPN, Load Balancing) in a cloud environment.
• Experience with identity and access management (IAM) in GCP and user management in Google Workspace.
• Proficiency in scripting languages (e.g., Python, Bash)
• Proficiency in executing the core Terraform workflow
• Expertise in managing Terraform state, including local and remote backends, state locking, and handling sensitive data.
• Experience with containerisation technologies (Docker, Kubernetes).
• Familiarity with CI/CD pipelines and DevOps principles.
• Excellent problem-solving and troubleshooting skills.
• Strong communication and interpersonal skills.

Preferred Qualifications

• Google Cloud certification (e.g., Professional Cloud Architect, Professional Cloud Engineer).
• Google Workspace certification (e.g., Google Workspace Administrator).
• Experience with hybrid cloud environments.
• Knowledge of database administration on GCP (e.g., Cloud SQL, Cloud Spanner).
• Experience with big data technologies on GCP (e.g., BigQuery, Dataflow).

66degrees is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to actual or perceived race, color, religion, sex, gender, gender identity, national origin, age, weight, height, marital status, sexual orientation, veteran status, disability status or other legally protected class.