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Assistant Aws Trainer Jobs (NOW HIRING)

Jobgether

$81K - $111K/yr

Experience with Amazon SageMaker for training, tuning, deploying, and monitoring ML models in ... These tools assist our recruitment team but do not replace human judgment. Final hiring decisions ...

Amazon

Data Center Chief Engineer, AWS

Boardman, OR

Provide training and guidance to Engineering Operations Technicians and responsible for working ... May assist in the build out of new facilities and assist in projects to increase current facility ...

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How much do assistant aws trainer jobs pay per year?

As of Jun 16, 2026, the average yearly pay for assistant aws trainer in the United States is $42,039.00, according to ZipRecruiter salary data. Most workers in this role earn between $24,000.00 and $50,500.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Assistant AWS Trainers, and how can they be addressed?

Assistant AWS Trainers often face challenges such as keeping up with the rapidly evolving AWS platform and adapting training materials to suit diverse learning styles. To overcome these, it's important to engage in continuous learning, attend AWS webinars or certification programs, and collaborate closely with senior trainers. Additionally, leveraging feedback from trainees and regularly updating course content can help ensure effective training sessions. Building strong communication skills and staying adaptable will also support success in this dynamic role.

What are the key skills and qualifications needed to thrive as an Assistant AWS Trainer, and why are they important?

To thrive as an Assistant AWS Trainer, you need a solid understanding of AWS cloud concepts, networking, and computing, usually backed by an AWS certification like AWS Certified Solutions Architect – Associate. Familiarity with AWS Management Console, CLI tools, and learning management systems is commonly required. Excellent communication, presentation, and patience are crucial soft skills for effectively delivering technical content to diverse learners. These skills ensure that trainees gain practical AWS knowledge and that training sessions are engaging and informative.

What is the difference between Assistant Aws Trainer vs Cloud Support Associate?

AspectAssistant Aws TrainerCloud Support Associate
CertificationsAWS Certified Cloud Practitioner or AWS Certified TrainerAWS Certified Solutions Architect or AWS Certified Cloud Practitioner
Work EnvironmentTraining centers, online platforms, corporate training sessionsCustomer support centers, technical help desks, cloud service providers
Employer & Industry UsageTraining companies, tech firms, educational institutionsCloud service providers, IT support companies, enterprise IT teams

The Assistant Aws Trainer primarily focuses on delivering AWS training and certifications, often working in educational or corporate training environments. In contrast, the Cloud Support Associate provides technical support and troubleshooting for AWS cloud services. While both roles require AWS certifications, their core responsibilities and work settings differ significantly.

What is an Assistant AWS Trainer?

An Assistant AWS Trainer is a professional who supports lead instructors in delivering training sessions on Amazon Web Services (AWS) technologies. They help organize course materials, assist with hands-on labs, answer student queries, and ensure a smooth learning experience. Assistant AWS Trainers often have foundational AWS knowledge and may work toward becoming certified trainers themselves. Their role is crucial in helping participants understand cloud concepts, deployment, and best practices. They act as a bridge between students and lead trainers to enhance overall training effectiveness.
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Assistant Aws Trainer jobs near you

Senior Data/ML Engineer (AWS)

Jobgether

Remote

$81K - $111K/yr

Full-time

Posted 4 days ago

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data/ML Engineer (AWS) based in Netherlands.

This role sits at the intersection of advanced data engineering and applied machine learning, focusing on building scalable, cloud-native data platforms on AWS. You will design and develop modern data lakes, streaming pipelines, and ML-driven services that power analytics and intelligent automation across enterprise systems. The position involves working with large-scale, multi-source datasets spanning operational, customer, and marketing domains. You will contribute to end-to-end data lifecycle design, from ingestion and transformation to model deployment and monitoring. The environment is highly collaborative, involving data engineers, ML engineers, DevOps, and architecture teams. This is an opportunity to shape production-grade data ecosystems that directly enable AI-driven business capabilities.

Accountabilities:

In this role, you will be responsible for designing and delivering scalable data and ML solutions that support enterprise-grade analytics and AI use cases.

  • Design and implement multi-zone data lake architectures on AWS using S3, including raw, curated, and analytics-ready layers aligned with enterprise requirements.
  • Build and maintain batch and real-time data pipelines using services such as AWS Glue, Kinesis, and Step Functions to integrate diverse data sources.
  • Develop ETL workflows, data transformations, and metadata management frameworks using AWS Glue Data Catalog and related tools.
  • Deploy and operationalize ML models using Amazon SageMaker for use cases such as prediction, scoring, and segmentation.
  • Integrate generative AI capabilities using Amazon Bedrock to enable intelligent automation, personalization, and enrichment workflows.
  • Support data migration initiatives from Azure to AWS, including schema mapping, validation, reconciliation, and performance optimization.
  • Implement data governance, security, and access controls using AWS Lake Formation and ensure compliance with data standards.
  • Collaborate with cross-functional teams to define architecture, maintain documentation, and ensure data quality across all pipelines and outputs.
Requirements:

The ideal candidate brings strong experience in cloud data engineering and applied machine learning within AWS environments.

  • 5+ years of experience in data engineering or ML engineering, with at least 2+ years working extensively on AWS.
  • Strong proficiency in Python and SQL with hands-on experience in building scalable data pipelines.
  • Deep knowledge of AWS services including S3, Glue, Athena, Kinesis, Lambda, and Step Functions.
  • Experience with Amazon SageMaker for training, tuning, deploying, and monitoring ML models in production.
  • Working knowledge of Amazon Bedrock or other generative AI frameworks for enterprise use cases.
  • Experience designing and maintaining data lake architectures with strong governance and security models.
  • Familiarity with Azure data platforms and cloud migration projects is highly desirable.
  • Strong understanding of data modeling, feature engineering, and ML integration best practices.
  • Excellent problem-solving, communication, and collaboration skills in Agile environments.
Benefits:
  • Competitive compensation package aligned with experience and expertise
  • Fully remote work opportunity
  • Exposure to cutting-edge AWS data and AI/ML technologies
  • Opportunity to work on large-scale enterprise data transformation programs
  • Collaborative and cross-functional global engineering environment
  • Career growth in advanced data engineering and machine learning domains
  • Flexible work culture supporting autonomy and ownership
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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