Senior Cloud Devops & Sre – Multi-Cloud K8S & Ci/Cd (Remote Latam)
Bluelightconsulting
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Descripción de la vacante
EY GDS is seeking a DataOps / Cloud DevOps Engineer to join our Cloud, Data & AI practice. The role involves building and maintaining scalable cloud environments, automation, and deployment frameworks to enable reliable delivery of business-critical solutions.
You will work with architects, data engineers, and developers to accelerate cloud application delivery, implement IaC with Terraform, and manage CI/CD pipelines across enterprise environments.
Formación
- Bachelor’s degree in computer science, software engineering or related field.
- 3–6 years in DevOps, Cloud/Platform Engineering or DataOps roles.
- Experience designing and maintaining CI/CD pipelines with GitHub Actions or similar.
Responsabilidades
- Design, develop, and maintain CI/CD pipelines for cloud apps, data platforms, and AI solutions.
- Implement and manage Infrastructure as Code using Terraform.
- Deploy and maintain cloud environments on Azure and AWS.
- Build Kubernetes-based platforms for containerized workloads.
- Automate deployments across development, testing, and production.
- Develop GitHub Actions workflows and deployment automation frameworks.
- Support CI/CD for Azure Functions, Web Apps, APIs, and Kubernetes services.
- Collaborate with architects, engineers, and data teams to improve reliability and scalability.
Conocimientos
Educación
Herramientas
Descripción del empleo
EY GDS is actively recruiting a DataOps /Cloud DevOps Engineer to join our growing Cloud, Data & AI practice. We are looking for a technology professional with experience supporting enterprise cloud platforms, data ecosystems, and modern application delivery through automation, Infrastructure as Code, and DevOps best practices.
The successful candidate will work closely with solution architects, cloud engineers, data engineers, application developers, and client stakeholders to build, automate, and maintain scalable cloud environments and deployment frameworks that enable reliable delivery of business-critical solutions.
As a DataOps /Cloud DevOps Engineer at EY GDS, you will help accelerate the delivery of cloud applications, analytics platforms, and AI solutions by implementing Infrastructure as Code, CI/CD pipelines, container platforms, monitoring capabilities, and operational excellence practices across enterprise environments.
Responsibilities
Design, develop, and maintain CI/CD pipelines supporting cloud applications, data platforms, and AI solutions.
Implement and manage Infrastructure as Code (IaC) using Terraform and cloud-native services.
Deploy, configure, and maintain enterprise cloud environments across Azure and/or AWS.
Build and support Kubernetes-based platforms for containerized workloads and microservices.
Automate application, infrastructure, and data platform deployments across development, testing, and production environments.
Develop and maintain GitHub Actions workflows and deployment automation frameworks.
Support ci/cd for cloud-native services including Azure Functions, Web Apps, APIs, Kubernetes Services, and other platform components.
Collaborate with solution architects, software developers, and data engineering teams to improve platform reliability, scalability, and deployment efficiency.
Implement monitoring, logging, alerting, and observability solutions across cloud platforms.
Support security, compliance, identity management, secrets management, and governance requirements.
Contribute to reusable deployment templates, engineering standards, and platform automation frameworks.
Promote DevOps and DataOps best practices, including source control, automated testing, release management, and operational excellence.
Required experience
3 to 6 years of experience in DevOps, Cloud Engineering, Platform Engineering, DataOps, or related roles.
Bachelor’s degree in computer science, Software Engineering, Information Technology, Data Engineering, or a related field.
Experience designing and maintaining CI/CD pipelines using GitHub Actions, Azure DevOps, GitLab CI/CD, or similar technologies.
Strong experience with Infrastructure as Code and Terraform.
Experience with Azure Kubernetes Service (AKS), Amazon EKS, or other Kubernetes platforms.
Experience with scripting and automation using Python, PowerShell, Bash, or similar languages.
Knowledge of cloud-native architectures and application hosting patterns.
Familiarity with enterprise data platforms and modern analytics ecosystems.
Understanding of cloud security, networking fundamentals, and operational best practices.
Experience working with Azure and/or AWS cloud platforms.
Excellent communication and stakeholder management skills.
Consulting mindset with the ability to adapt to different client environments and technology stacks.
We are looking for passionate individuals who enjoy building and automating modern cloud platforms that power applications, data products, and AI solutions.
We are looking for a Senior DevOps Engineer with strong expertise in AWS, infrastructure automation, CI/CD, and managing high-availability, high-throughput, low-latency production environments.
The ideal candidate will ensure infrastructure scalability, reliability, security, and cost efficiency while supporting mission-critical systems operating 24/7.
Experience: 5+ years in DevOps, SRE, or Platform Engineering, supporting 24/7 production environments.
Advanced AWS: ECS/Fargate, ALB/NLB, Auto Scaling, VPC, Transit Gateway, Route 53, ACM, CloudFront, IAM, KMS, Secrets Manager, SSM, and CloudTrail across multiple AWS accounts.
Infrastructure as Code: Advanced Terraform expertise, including reusable versioned modules, S3 remote state, version pinning, and multi-environment deployments (Dev, QA, Integration, Prod).
Containerization: Docker, Dockerfiles, ECR image management, base images, and ECS task definitions.
CI/CD: Jenkins, Groovy, Jenkinsfiles, shared libraries, Java/Maven builds, and Shift-Left security practices.
Streaming & Data Infrastructure: Production experience with Kafka (AWS MSK), Aerospike, and Multi-AZ architectures. Experience with EMR/EMR Serverless, Flink, Airflow, Athena, and S3 Tables.
Monitoring & Observability: Prometheus, Grafana, Graphite, CloudWatch, Fluent Bit, Logstash, OpenSearch, Slack, and SNS alerting.
Automation: Strong Python (boto3), Bash scripting, and AWS Lambda.
Security: Vulnerability management, system patching, credential protection, API key security, and least-privilege access.
Tools & Collaboration: Git, Pull Requests, Jira, Confluence, and AI-powered development tools.
Strong problem-solving skills, independent work capabilities, proactive communication, and data-driven decision-making.
We are looking for a Senior DevOps Engineer with strong expertise in AWS, infrastructure automation, CI/CD, and managing high-availability, high-throughput, low-latency production environments.
The ideal candidate will ensure infrastructure scalability, reliability, security, and cost efficiency while supporting mission-critical systems operating 24/7.
Requisitos
Experience: 5+ years in DevOps, SRE, or Platform Engineering, supporting 24/7 production environments.
Advanced AWS: ECS/Fargate, ALB/NLB, Auto Scaling, VPC, Transit Gateway, Route 53, ACM, CloudFront, IAM, KMS, Secrets Manager, SSM, and CloudTrail across multiple AWS accounts.
Infrastructure as Code: Advanced Terraform expertise, including reusable versioned modules, S3 remote state, version pinning, and multi-environment deployments (Dev, QA, Integration, Prod).
Containerization: Docker, Dockerfiles, ECR image management, base images, and ECS task definitions.
CI/CD: Jenkins, Groovy, Jenkinsfiles, shared libraries, Java/Maven builds, and Shift-Left security practices.
Streaming & Data Infrastructure: Production experience with Kafka (AWS MSK), Aerospike, and Multi-AZ architectures. Experience with EMR/EMR Serverless, Flink, Airflow, Athena, and S3 Tables.
Monitoring & Observability: Prometheus, Grafana, Graphite, CloudWatch, Fluent Bit, Logstash, OpenSearch, Slack, and SNS alerting.
Automation: Strong Python (boto3), Bash scripting, and AWS Lambda.
Security: Vulnerability management, system patching, credential protection, API key security, and least-privilege access.
Tools & Collaboration: Git, Pull Requests, Jira, Confluence, and AI-powered development tools.
Strong problem-solving skills, independent work capabilities, proactive communication, and data-driven decision-making.
Design, deploy, and maintain scalable, secure, highly available AWS infrastructure.
Manage containerized workloads using ECS/Fargate, ALB/NLB, and autoscaling.
Develop and maintain reusable Terraform modules and Jenkins/Groovy CI/CD pipelines.
Operate and optimize streaming platforms, data infrastructure, and distributed systems.
Implement monitoring, logging, alerting, and proactive incident resolution.
Continuously optimize AWS costs through resource right-sizing, waste reduction, and cost-conscious architecture decisions.
Automate operational processes using Python, Bash, and AWS Lambda.
Strengthen infrastructure security, vulnerability management, and CI/CD security controls.
Own infrastructure projects end-to-end, from design and deployment to documentation and ongoing support.
Create clear technical documentation and step-by-step runbooks for first-level support teams.
Manage infrastructure changes through reviewed Pull Requests using a single main branch.
Use performance metrics, operational data, and cost analysis to guide technical decisions and advise leadership.
Leverage AI tools to improve productivity while maintaining code quality and review standards.
Experience in AdTech or Real-Time Bidding (RTB) environments.
AWS CloudFormation.
Java development experience.
Cloud AI Engineer, Google Cloud (English)
Share Cloud AI Engineer, Google Cloud (English)
_corporate_fare_ Google _place_ Buenos Aires, Argentina; Mexico City, CDMX, Mexico
**Mid**
Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.
Share Cloud AI Engineer, Google Cloud (English)
_info_outline_
XIn most instances, this position requires in-person interviews as part of the hiring process.
Only applications of candidates with Mexican citizenship will be evaluated for this role in compliance with the provisions of Article 7 of the Federal Labor Law.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: **Buenos Aires, Argentina; Mexico City, CDMX, Mexico** .
**Minimum qualifications:**
+ Bachelor's degree in Computer Science or equivalent practical experience.
+ 3 years of experience building machine learning solutions and working with technical customers.
+ Experience designing cloud enterprise solutions and supporting customer projects to completion.
+ Experience building and deploying custom ML models into production, including experience with deep learning frameworks and with designing and deploying agentic AI workflows for business process automation.
+ Experience coding in Python, including data structures, algorithms, and software design.
+ Ability to communicate in English fluently as this is a customer-facing role.
**Preferred qualifications:**
+ Experience working with recommendation engines, data pipelines, or distributed machine learning.
+ Experience with deep learning frameworks (e.g., TensorFlow, PyTorch, XGBoost).
+ Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, Pig, Hive, MapReduce, Flume).
+ Understanding of the auxiliary practical concerns in production machine learning systems.
**About the job**
The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google's global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners.
As a Cloud AI Engineer, you will design and implement machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and Vertex AI. You will work with customers to identify opportunities to apply machine learning in their business, and travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. Additionally, you will work closely with Product Management and Product Engineering to build and constantly drive excellence in our products.
In this role, you will work with key Google Cloud customers. Together with the team you will support customer implementation of Google Cloud products through: architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and much more.
Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
**Responsibilities**
+ Be a trusted technical advisor to customers and solve complex machine learning challenges.
+ Coach customers on the practical challenges in machine learning systems: feature extraction and feature definition, data validation, monitoring, and management of features and models.
+ Work with Customers, Partners, and Google Product teams to deliver tailored solutions into production.
+ Create and deliver best practice recommendations, tutorials, blog articles, and sample code.
+ Travel up to 30% in-region for meetings, technical reviews, and onsite delivery activities.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See alsoGoogle's EEO Policy ( ,Know your rights: workplace discrimination is illegal ( ,Belonging at Google ( , andHow we hire ( .
If you have a need that requires accommodation, please let us know by completing ourAccommodations for Applicants form ( .
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.
Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, and subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity and Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also and If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form:
Senior Global Sales Operations and AI Solutions Consultant, Google Cloud (English, Spanish)
Share Senior Global Sales Operations and AI Solutions Consultant, Google Cloud (English, Spanish)
_corporate_fare_ Google _place_ Mexico City, CDMX, Mexico; Buenos Aires, Argentina; +2 more; +1 more
**Advanced**
Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders; deep expertise in domain.
Share Senior Global Sales Operations and AI Solutions Consultant, Google Cloud (English, Spanish)
_info_outline_
X
Only applications of candidates with Mexican citizenship will be evaluated for this role in compliance with the provisions of Article 7 of the Federal Labor Law.
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: **Mexico City, CDMX, Mexico; Buenos Aires, Argentina; São Paulo, Brazil** .
**Minimum qualifications:**
+ Bachelor's degree or equivalent practical experience.
+ 10 years of experience managing B2B business development or inside sales operations within the technology industry.
+ Experience designing scalable operating models that integrate internal teams with external partner ecosystems.
+ Ability to communicate in English and Spanish fluently to support client relationship management in this region.
**Preferred qualifications:**
+ Experience as a problem solver seeking to find and solve business problems and embrace continuous improvement, using data-driven decision making.
+ Experience creating and implementing AI tools, automation, or digital transformation projects that resulted in measurable workflow efficiencies.
+ Experience with sales pipeline forecasting and leveraging data analytics to predict and meet revenue goals.
+ Understanding of modern commercial models, with a focus on creating and executing innovative, outcome-based, or gain-share statements of work (SOWs).
+ Proven track record in an operational consulting or client-facing advisory role, with verified success in influencing executives and driving large-scale change management.
**About the job**
The Cloud Vendor Management Organization (VMO) is at the forefront of Google Cloud's mission to accelerate our customers' digital transformation. We deliver enterprise-grade solutions leveraging Google's technology on the cleanest cloud in the industry.
As a part of the VMO, you will step away from legacy vendor oversight and instead act as a strategic solution consultant, co-creating high-efficiency solutions with our delivery partners. You will be pivotal in reshaping a modern vendor ecosystem that leverages AI and smart governance to support our global growth and solve critical business problems for customers across the global customer landscape.
As the Global Sales Operations and AI Solutions Consultant for Cloud VMO, you will transcend traditional vendor management to serve as a strategic consultant and transformation ally to Google Cloud's sales leadership. In this role, you will lead the evolution of our Business Development and inside Sales programs into highly automated, high-velocity engines. You will not just manage suppliers; you will co-create next-generation sales workflows alongside our strategic partners.
By embedding an AI-first approach, designing smart governance frameworks, and radically transforming business workflows, you will drive exponential operational efficiency. This role requires a sophisticated blend of sales operations expertise, consulting acumen, and a deep understanding of how to leverage the emerging AI landscape to scale pipeline and business. Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
**Responsibilities**
+ Move beyond traditional vendor management to co-create and architect delivery models with strategic partners. Collaborate with suppliers to redesign their internal workflows, embedding modern technologies.
+ Act as a management consultant to Google Cloud sales leadership. Design and architect complex extended workforce engagements, determining optimal delivery frameworks that seamlessly integrate internal ecosystems with partner capabilities.
+ Identify, scope, and implement opportunities to embed AI-driven automation, GenAI tools, and advanced technology stacks into the partner ecosystem.
+ Advocate operational excellence across the business funnel. Identify systemic operational gaps, design scaled workflows, and continuously optimize ecosystem performance to improve conversion rates and maximize agreement win rates.
+ Establish modern, data-driven governance frameworks that prioritize business outcomes over mere compliance. Lead executive business reviews using predictive data to drive accountability for monthly/quarterly goals, including opportunity creation and pipeline ACV.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of
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