Green Card Aws Data Engineer Jobs
AWS Data Engineer roles qualify for EB-2 and EB-3 green card sponsorship through PERM labor certification, which requires employers to document recruitment efforts before filing your I-140 petition. Cloud data infrastructure skills map cleanly to DOL specialty occupation standards, making this one of the more employer-familiar paths to permanent residency sponsorship.
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Corporate Functions Senior AWS Cloud Engineer – VP III
Who We Are Looking For
We are seeking a highly experienced, hands-on technology leader to serve as the Corporate Functions Senior AWS Cloud Engineer – VP III, responsible for designing, engineering, deploying, and supporting complex AWS-based applications and AI-enabled platforms across Corporate Functions Technology.
This role is intended for a senior cloud engineer who can operate as a principal-level technical contributor with deep hands-on expertise across the AWS ecosystem. The successful candidate will be responsible for building secure, scalable, production-ready cloud solutions that support enterprise applications, intelligent assistants, AI-enabled workflows, automation, integrations, data services, and operationally resilient platforms.
The ideal candidate has extensive experience deploying end-to-end applications into AWS, including networking, compute, application hosting, load balancing, security, data services, secrets management, observability, CI/CD, and production support. This individual must also have hands-on experience enabling AI capabilities within AWS, including Amazon Bedrock, AI service integrations, model endpoint connectivity, AI orchestration patterns, and secure deployment of AI-enabled applications.
This is not a purely advisory or architecture-only role. The candidate must be able to actively engineer, configure, deploy, troubleshoot, automate, and support complex AWS environments while also guiding other engineers and development teams on cloud-native engineering best practices.
Why This Role Matters
Corporate Functions is expanding the use of cloud-native technologies, AI-powered business capabilities, intelligent automation, and modern application platforms across HR, Legal, Audit, Compliance, Risk, Realty, and other business domains.
This role will help establish the engineering foundation required to:
- Deploy secure, scalable, and resilient applications into AWS.
- Enable AI-powered applications and intelligent business workflows.
- Support enterprise-grade architectures across application, data, integration, security, and observability layers.
- Implement reusable AWS engineering patterns that accelerate delivery.
- Improve cloud security, operational resilience, and production maturity.
- Support modernization of legacy platforms into cloud-native and AI-enabled solutions.
- Partner across application, architecture, cybersecurity, infrastructure, and business teams to deliver measurable business value.
This is a highly visible senior engineering role that will directly influence how Corporate Functions builds, deploys, and operates modern AWS and AI-enabled solutions.
What You Will Be Responsible For
1. AWS Cloud Engineering & Architecture
- Design, engineer, deploy, and support complex AWS solutions for enterprise business applications.
- Build secure, highly available, scalable, and resilient cloud environments.
- Implement AWS architectures across multiple availability zones.
- Establish reusable AWS reference architectures, deployment patterns, and engineering standards.
- Lead cloud modernization efforts for applications moving into AWS.
- Partner with architects and application teams to translate business and platform requirements into production-ready cloud solutions.
- Provide hands-on engineering leadership across design, build, release, troubleshooting, and support activities.
2. End-to-End AWS Application Deployment
- Deploy enterprise applications into AWS from infrastructure setup through production release.
- Engineer complete application environments across:
- VPC and network configuration
- Private and application subnets
- Load balancing
- Compute services
- Application hosting
- Data services
- Secrets and certificate management
- Monitoring and alerts
- Security controls
- CI/CD automation
- Support backend application deployment patterns including Tomcat, Java services, APIs, microservices, containers, and serverless workloads.
- Troubleshoot complex application, infrastructure, networking, and security issues.
- Ensure applications are production-ready, operationally supportable, and aligned with enterprise standards.
3. Required AWS Platform Expertise
Serve as a subject matter expert across core AWS services, including:
- VPC
- Subnets
- Security Groups
- Route 53
- Application Load Balancer
- Auto Scaling Groups
- EC2
- ECS
- EKS
- Lambda
- API Gateway
- EventBridge
- Step Functions
- RDS
- Aurora
- PostgreSQL
- ElastiCache / Redis
- S3
- Secrets Manager
- Certificate Manager
- CloudWatch
- CloudTrail
- IAM
- Systems Manager
- VPC Endpoints
- PrivateLink
The candidate must be able to configure, deploy, troubleshoot, and support these services in complex enterprise environments.
4. AWS AI Engineering & Intelligent Application Enablement
- Design and deploy AWS-based AI-enabled applications and intelligent business platforms.
- Implement AI solutions using AWS-native services, including Amazon Bedrock and related AI/ML capabilities.
- Integrate applications with LLMs, model endpoints, AI services, enterprise APIs, and internal AI platforms.
- Engineer secure patterns for AI service invocation, prompt processing, response handling, audit logging, and operational monitoring.
- Support AI-enabled applications that interact with users, enterprise systems, workflow engines, databases, and external services.
- Implement responsible AI engineering controls including observability, traceability, guardrails, human oversight, logging, and escalation patterns.
- Partner with architecture, cybersecurity, data, risk, and business teams to ensure AI capabilities are secure, compliant, scalable, and operationally mature.
5. AWS-Native AI Orchestration & Agentic Patterns
- Build and support AWS-native orchestration patterns for AI-enabled workflows.
- Implement solutions leveraging:
- Amazon Bedrock
- Lambda
- Step Functions
- EventBridge
- API Gateway
- CloudWatch
- Secrets Manager
- IAM
- VPC Endpoints
- AWS-hosted application services
- Support enterprise AI deployment patterns involving tool calling, workflow orchestration, event-driven processing, and secure backend service execution.
- Engineer integration patterns that allow AI-enabled applications to interact with enterprise systems and business processes.
- Support Agent-to-Agent and system-to-system integration patterns where AI capabilities need to coordinate across internal and external platforms.
- Ensure AI workloads are observable, secure, auditable, resilient, and aligned with enterprise governance requirements.
6. Infrastructure Automation & DevOps
- Develop and maintain Infrastructure as Code for AWS environments.
- Automate environment provisioning, application deployment, configuration, and release management.
- Build and support CI/CD pipelines for cloud-native and AI-enabled applications.
- Partner with development teams to streamline deployment processes.
- Improve engineering productivity through reusable templates, automation scripts, and deployment patterns.
- Support DevOps, SRE, and operational excellence practices across cloud environments.
7. Security, Secrets Management & Cloud Governance
- Implement security controls across AWS application environments.
- Configure IAM roles, policies, access controls, encryption, secrets, certificates, and secure service-to-service communication.
- Support VPC endpoint and PrivateLink patterns for private connectivity.
- Ensure cloud environments meet enterprise standards for cybersecurity, data protection, auditability, resiliency, and compliance.
- Partner with Cybersecurity, Cloud Governance, Enterprise Architecture, Risk, and Infrastructure teams.
- Support architecture reviews, cloud governance approvals, risk assessments, and production readiness processes.
8. Monitoring, Observability & Production Support
- Implement monitoring, logging, tracing, alerting, and observability solutions for AWS-hosted applications.
- Utilize tools such as:
- CloudWatch
- CloudTrail
- Prometheus
- Grafana
- Application logs
- Infrastructure metrics
- Health checks
- Build dashboards and operational views for application and infrastructure support.
- Perform root cause analysis and lead resolution of complex production issues.
- Develop runbooks, operational procedures, monitoring standards, and support documentation.
- Improve platform reliability, incident response, and operational maturity.
9. Enterprise Integration & Application Connectivity
- Support secure integrations between AWS-hosted applications and enterprise platforms.
- Build and support integration patterns involving:
- Internal enterprise applications
- Workday
- ServiceNow
- Microsoft 365
- SharePoint
- Vendor SaaS platforms
- Enterprise AI platforms
- Data and reporting platforms
- Implement API-based, scheduled, event-driven, and service-to-service integration patterns.
- Ensure integrations are reliable, secure, observable, and production-ready.
- Troubleshoot complex connectivity, authentication, data flow, and application interaction issues.
10. Technical Leadership & Engineering Excellence
- Serve as a senior AWS engineering authority across Corporate Functions Technology.
- Provide technical guidance to development teams, cloud engineers, data engineers, and delivery partners.
- Lead technical design reviews, deployment reviews, code reviews, and operational readiness assessments.
- Establish AWS engineering standards, reusable patterns, and best practices.
- Mentor engineers on cloud-native development, AI deployment patterns, observability, security, automation, and production support.
- Influence technical direction across multiple Corporate Functions initiatives.
Must-Have Qualifications
- 12+ years of experience in software engineering, cloud engineering, platform engineering, infrastructure engineering, or enterprise application delivery.
- 8+ years of hands-on AWS engineering experience.
- Proven experience deploying complex enterprise applications end-to-end into AWS.
- Deep hands-on expertise with AWS networking, compute, security, data services, observability, and automation.
- Strong experience designing and implementing secure multi-tier AWS architectures.
- Required experience with AWS services including:
- VPC
- Subnets
- Security Groups
- Application Load Balancer
- EC2
- ECS / EKS
- Lambda
- API Gateway
- EventBridge
- Step Functions
- RDS / Aurora / PostgreSQL
- ElastiCache / Redis
- S3
- Secrets Manager
- Certificate Manager
- CloudWatch
- CloudTrail
- IAM
- VPC Endpoints / PrivateLink
- Required experience building or deploying AI-enabled applications within AWS.
- Required experience with Amazon Bedrock or comparable cloud-based AI service integration.
- Experience integrating applications with LLMs, model endpoints, enterprise AI platforms, or AI orchestration layers.
- Strong understanding of AI deployment patterns, including prompt processing, service invocation, audit logging, observability, and responsible AI controls.
- Experience with Infrastructure as Code, CI/CD pipelines, automated deployments, and DevOps practices.
- Strong troubleshooting experience across cloud infrastructure, application services, networking, security, and production operations.
- Ability to lead technical teams and influence engineering decisions without requiring direct management authority.
- Strong communication skills with the ability to explain complex technical topics to application teams, architects, risk partners, and senior stakeholders.
Preferred Qualifications
- Experience with Databricks.
- Experience building data pipelines, lakehouse solutions, or enterprise data processing frameworks.
- Experience integrating AWS-hosted applications with enterprise data platforms.
- Experience with Java, Python, SQL, or modern backend development frameworks.
- Experience with containerized workloads and Kubernetes-based deployments.
- Experience with Agent-to-Agent integration patterns, enterprise AI orchestration, or workflow-driven AI solutions.
- Experience supporting Corporate Functions domains such as HR, Legal, Audit, Compliance, Risk, Security, Realty, or Finance.
- Experience within financial services or another highly regulated industry.
- AWS Professional-level certifications strongly preferred.
- AWS AI/ML, Security, DevOps, or Architecture certifications preferred.
- Databricks certification is a plus.
What We Value
- Deep hands-on AWS engineering capability.
- Ability to build and operate complex solutions, not just design them.
- Strong understanding of AI-enabled application patterns.
- Practical cloud security and production support mindset.
- Strong ownership and accountability.
- Ability to simplify complex technical challenges.
- Engineering excellence and attention to detail.
- Continuous learning and innovation.
- Strong partnership across business, application, architecture, cybersecurity, infrastructure, and data teams.
- Ability to mentor others and raise the overall technical maturity of the organization.
Salary Range:
$110,000 - $207,500 Annual
The range quoted above applies to the role in the primary location specified. If the candidate would ultimately work outside of the primary location above, the applicable range could differ.
Employees are eligible to participate in State Street’s comprehensive benefits program, which includes: our retirement savings plan (401K) with company match; insurance coverage including basic life, medical, dental, vision, long-term disability, and other optional additional coverages; paid-time off including vacation, sick leave, short term disability, and family care responsibilities; access to our Employee Assistance Program; incentive compensation including eligibility for annual performance-based awards (excluding certain sales roles subject to sales incentive plans); and, eligibility for certain tax advantaged savings plans.
About State Street
Across the globe, institutional investors rely on us to help them manage risk, respond to challenges, and drive performance and profitability. We keep our clients at the heart of everything we do, and smart, engaged employees are essential to our continued success.
We are committed to fostering an environment where every employee feels valued and empowered to reach their full potential. As an essential partner in our shared success, you’ll benefit from inclusive development opportunities, flexible work-life support, paid volunteer days, and vibrant employee networks that keep you connected to what matters most. Join us in shaping the future.
As an Equal Opportunity Employer, we consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.
Job Application Disclosure:
It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
See all 443+ Green Card Aws Data Engineer Jobs
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Get Access To All JobsTips for Finding Green Card Sponsorship as an Aws Data Engineer
Align your credentials with EB-2 requirements
A master's degree in computer science, data engineering, or a related field positions you for EB-2 sponsorship. If you hold a bachelor's plus five years of progressive AWS-specific experience, document each role with detailed job duties to support an advanced-degree equivalency argument.
Research employers with active PERM filing history
Target companies that have filed PERM applications for data engineering roles before. DOL disclosure data shows which employers have completed the recruitment and prevailing-wage process, reducing your risk of working for an employer unfamiliar with the full EB-2 or EB-3 pipeline.
Use Migrate Mate to find green card-sponsoring roles
Filter your AWS Data Engineer job search by employers with green card sponsorship history using Migrate Mate. This surfaces companies already familiar with PERM filings for data roles, so you spend less time screening employers who have never navigated employment-based sponsorship.
Verify your offered wage meets DOL prevailing levels
Before signing an offer, check the OFLC Wage Search to confirm your offered salary meets the prevailing wage for your job zone and work location. A wage set below DOL Level I or II thresholds can delay LCA certification and stall your entire PERM timeline.
Understand how the PERM recruitment window affects your start date
PERM requires your employer to complete a formal 30-day recruitment period before filing. If you're transitioning from an expiring H-1B visa or OPT, align your offer acceptance timeline so the PERM filing begins before your current authorization runs short.
Clarify AWS-specific job duties in your PERM description
DOL audits often target vague job descriptions on PERM applications. Work with your employer to include specific AWS services you'll manage, such as Redshift, Glue, or EMR, so the role clearly requires a specialized degree rather than general IT skills.
Green Card Aws Data Engineer: Frequently Asked Questions
Does an AWS Data Engineer role qualify for EB-2 or EB-3 sponsorship?
AWS Data Engineer positions typically qualify for both EB-2 and EB-3, depending on your credentials and the employer's job requirements. EB-2 applies when the role requires a master's degree or equivalent, which is common in data engineering. EB-3 covers roles requiring a bachelor's degree. O*NET classifies data engineering work in Job Zone 4, supporting specialty occupation arguments under either category.
How does green card sponsorship differ from H-1B sponsorship for this role?
H-1B sponsorship is temporary and subject to annual lottery selection, while PERM-based green card sponsorship leads to permanent residency with no lottery. The PERM process requires DOL labor certification and typically takes one to three years before an I-140 is approved, but once your priority date is current, you gain a direct path to lawful permanent residence rather than repeating visa cycles.
How long does the PERM process take for a data engineering role?
PERM labor certification for AWS Data Engineer positions currently averages six to eighteen months at DOL, depending on whether the application is audited. After PERM approval, your employer files the I-140 petition with USCIS, which adds several more months under standard processing. Candidates born in countries without significant visa backlogs can often complete the full green card process in two to four years.
Where can I find employers who sponsor green cards for AWS Data Engineers?
Migrate Mate lets you search for AWS Data Engineer jobs filtered by employers with documented green card sponsorship history. This is more reliable than filtering by job postings that mention sponsorship without any filing history behind them, since PERM filings are publicly disclosed through DOL and you can confirm an employer's track record before investing time in their process.
Can my employer start PERM while I'm on H-1B status?
Yes, employers can file PERM on your behalf while you remain on H-1B status. Starting early matters because AC21 portability protections kick in once your I-140 is approved and your PERM has been pending for 180 days, giving you flexibility to change roles without losing your priority date. USCIS allows you to maintain H-1B extensions in three-year increments once the I-140 is approved.