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Cloud Engineer

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Cloud Engineer

Azure Data Engineer

Jobgether

Remote

Apply on the employer's site

Role description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Azure Data Engineer based in Switzerland.
This role offers the opportunity to strengthen cybersecurity operations by engineering reliable, scalable security data pipelines across cloud and on-premises environments.

You will work with high volumes of security telemetry and help ensure critical data is available for threat detection, incident response, compliance, and cyber risk visibility.

The position combines hands-on data engineering with cybersecurity, cloud technologies, automation, and data quality management.

You’ll collaborate with application, infrastructure, security, governance, and vendor teams to onboard and optimize diverse data sources.

The role is well suited to an engineer who enjoys troubleshooting complex ingestion challenges and improving system reliability and efficiency.

You’ll operate in a highly regulated financial services environment where data integrity, security, and operational excellence are essential.

This is an opportunity to make a direct impact on the organization’s ability to detect, investigate, and respond to cyber threats.

Accountabilities

  • Design, build, and maintain scalable security data ingestion pipelines for SIEM and cloud data platforms, including Azure Data Explorer and Log Analytics.
  • Parse, normalize, transform, enrich, and validate structured and unstructured security telemetry using regex, JSON parsing, schema mapping, and other data-processing techniques.
  • Partner with application owners, infrastructure and cloud teams, vendors, security stakeholders, and other internal groups to onboard new log sources and validate end-to-end data flows.
  • Ensure the integrity, completeness, timeliness, and quality of security telemetry used for monitoring, detection, incident response, reporting, and risk management.
  • Align security data with established schemas, naming conventions, governance standards, and organizational requirements to support downstream analytics and automation.
  • Troubleshoot ingestion, parsing, transformation, schema, and data-quality issues across diverse platforms and environments.
  • Maintain clear documentation covering log onboarding procedures, source requirements, data mappings, pipeline configurations, and operational support processes.
  • Collaborate with detection engineering and security operations teams to ensure telemetry supports investigation, threat detection, response, and cyber risk use cases.
  • Conduct telemetry gap analyses, identify missing or incomplete data sources, and recommend priorities for improving security coverage.
  • Support logging practices that meet regulatory, audit, compliance, retention, and data-integrity requirements.
  • Improve ingestion frameworks, automation, and onboarding processes to increase scalability, repeatability, reliability, and cost efficiency.
  • Support infrastructure-as-code, scripting, and automation initiatives that streamline deployment and ongoing pipeline maintenance.
  • Monitor pipeline performance and work with stakeholders to optimize ingestion reliability, throughput, and operational costs.
  • Stay current with emerging cybersecurity telemetry formats, logging standards, data engineering practices, and cloud security data-platform capabilities.

Requirements

  • 3+ years of relevant experience in cybersecurity, data engineering, log management, security operations, or a related technology discipline.
  • Hands-on experience onboarding, managing, and validating log sources within SIEM, cloud data platforms, or security analytics environments.
  • Strong understanding of data parsing, normalization, transformation, and validation, including experience with regex, JSON, XML, CSV, and both structured and unstructured data.
  • Familiarity with security telemetry from network, endpoint, identity, application, cloud, and infrastructure environments.
  • Experience working with cloud platforms and associated logging, monitoring, and analytics services, particularly within the Azure ecosystem.
  • Strong troubleshooting and analytical skills, with the ability to diagnose pipeline, ingestion, schema, and data-quality problems.
  • Understanding of compliance and regulatory requirements related to logging, retention, auditability, and data integrity.
  • Experience with scripting or automation technologies such as Python, PowerShell, or similar tools is preferred.
  • Familiarity with query languages used to validate, investigate, and analyze ingested security data.
  • Ability to coordinate complex onboarding initiatives across internal teams, vendors, and multiple stakeholders.
  • Strong organizational skills and the ability to balance operational support, project delivery, and continuous improvement.
  • Exceptional attention to detail and a strong sense of ownership for data quality and technical outcomes.
  • Broader cybersecurity experience in areas such as threat detection, incident response, vulnerability management, or cloud security is an advantage.
  • Strong communication, collaboration, judgment, and accountability, with the ability to work effectively within global teams.

Benefits

  • Remote work opportunity from anywhere.
  • Opportunity to work on cybersecurity data engineering within a highly regulated financial services environment.
  • Exposure to large-scale security telemetry, SIEM platforms, Azure data services, cloud environments, and security operations.
  • Hands-on opportunities to develop scalable pipelines, automation, infrastructure-as-code, and data-quality solutions.
  • Cross-functional collaboration with cybersecurity, cloud, infrastructure, application, governance, and vendor teams.
  • Opportunity to contribute directly to threat detection, incident response, compliance, and cyber risk visibility.
  • Professional growth through exposure to evolving cloud security, telemetry, and data engineering technologies.
  • A collaborative global working environment with opportunities to solve complex technical challenges.

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.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. 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.

This is a saved copy of a posting published elsewhere. Postings get taken down without notice — check the employer's site before applying. mentors.coach is not the hiring party.

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Cloud Engineer

Senior Infrastructure Engineer, AI/ML Systems

Portfolium (Acquired by Instructure)

Remotefulltime

Apply on the employer's site

Role description

At Instructure
, we believe in the power of people to grow and succeed throughout their lives. Our goal is to amplify that power by creating intuitive products that simplify learning and personal development, facilitate meaningful relationships, and inspire people to go further in their education and careers.

We do this by giving smart, creative, passionate people opportunities to create awesome. And that's where you come in:

Our AI team is where a lot of that gets built: applying advanced AI to real problems in learning, and turning research into product capabilities that educators and students use every day.

This is a hands-on delivery role. You'll build the deployment path that takes models and AI services from prototype to production, and you'll keep them running once they're there. You'll be one of two engineers who own infrastructure for this team, which means wide scope, real ownership, and direct influence over how we build.

You'll work closely with data scientists, applied AI engineers, and product partners to turn advanced AI ideas into reliable product capabilities used at scale.

What You'll Do

  • Build and operate deployment pipelines for AI services, covering CI/CD, infrastructure-as-code, environment promotion, and rollback
  • Deploy and operate model serving, batch scoring, and orchestration pipelines across development, staging, and production
  • Partner with data scientists and applied AI engineers to take prototypes into production, including system design for net-new services
  • Own production reliability for AI services: monitoring, alerting, debugging, performance, and cost
  • Spot repeated patterns and turn them into reusable templates, so the team can ship its second and third variant of something without rebuilding it

What You'll Need

  • Six or more years in infrastructure, DevOps, platform, or ML engineering, with ownership of systems running in production
  • Deep hands-on experience across a wide range of AWS services, including compute, networking, storage, deployment, and monitoring
  • Infrastructure-as-code experience (Terraform, CDK, or CloudFormation)
  • Experience with containers and modern deployment patterns (Docker required, Kubernetes or ECS/EKS a plus), applied to CI/CD pipelines you've designed and operated for production services
  • Experience with orchestration and workflow tooling (Airflow, Dagster, Argo, Step Functions, or similar)
  • Comfort working through ambiguity and collaborating directly with data scientists and researchers

It Would Be a Bonus If You Had

  • Experience with ML platform components and data pipeline orchestration at scale
  • Experience running LLM-based or retrieval-based systems in production
  • Experience operating specialized data stores, including graph databases
  • Experience building internal tooling, templates, or reference implementations that other engineers adopted

Onsite Collaboration Requirement:
This role requires working onsite on Tuesday and Wednesday, with Thursday strongly encouraged as part of our company’s in-person collaboration model.

Why Join Us

Join us and help shape the future of education by turning cutting-edge AI into reliable product capabilities.

At Instructure, we're on a mission to help educators and students learn together, anytime, anywhere, and however works best. You'll join our research-driven team tackling education's biggest challenges with cutting-edge technology.

We value diversity, creativity, and passion, and invest in our teams through mentorship, hack weeks, internal conferences, and a culture where innovation thrives. Here, you'll have the chance to build the next generation of LMS features that make a real impact on students and teachers, and do it in a collaborative, supportive environment that encourages experimentation and growth.

Get in on all the awesome at Instructure!
We offer competitive, meaningful benefits in every country where we operate. While they vary by location, here's a general idea of what you can expect:

  • Competitive compensation, plus all full-time employees participate in our ownership program - because everyone should have a stake in our success.
  • Flexible work culture. Our remote, hybrid and in-office collaboration spaces vary by role, team and location.
  • Generous time off, including local holidays and our annual “Dim the Lights” period in late December, when teams are encouraged to step back and recharge based on departmental needs.
  • Comprehensive wellness programs and mental health support
  • Learning and development resources, including professional development tools and tuition reimbursement, to support your growth
  • The technology and tools you need to do your best work
  • Motivosity employee recognition program
  • A culture rooted in inclusivity, support, and meaningful connection

We believe in hiring great people and treating them right. The more diverse we are, the better our ideas and outcomes.

Instructure is an Equal Opportunity Employer. We comply with applicable employment and anti-discrimination laws in every country where we operate.

All employees must pass a background check as part of the hiring process. To help protect our teams and systems, we’ve implemented identity verification measures. Candidates may be asked to verify their legal name, current physical location, and provide a valid contact number and residential address, in accordance with local data privacy laws.

Any attempt to misrepresent personal or professional information will result in disqualification.

This is a saved copy of a posting published elsewhere. Postings get taken down without notice — check the employer's site before applying. mentors.coach is not the hiring party.

Cloud Engineer

Senior Infrastructure Engineer, AI/ML Systems

Instructure

Remotefulltime

Apply on the employer's site

Role description

At Instructure
, we believe in the power of people to grow and succeed throughout their lives. Our goal is to amplify that power by creating intuitive products that simplify learning and personal development, facilitate meaningful relationships, and inspire people to go further in their education and careers.

We do this by giving smart, creative, passionate people opportunities to create awesome. And that's where you come in:

Our AI team is where a lot of that gets built: applying advanced AI to real problems in learning, and turning research into product capabilities that educators and students use every day.

This is a hands-on delivery role. You'll build the deployment path that takes models and AI services from prototype to production, and you'll keep them running once they're there. You'll be one of two engineers who own infrastructure for this team, which means wide scope, real ownership, and direct influence over how we build.

You'll work closely with data scientists, applied AI engineers, and product partners to turn advanced AI ideas into reliable product capabilities used at scale.

What You'll Do

  • Build and operate deployment pipelines for AI services, covering CI/CD, infrastructure-as-code, environment promotion, and rollback
  • Deploy and operate model serving, batch scoring, and orchestration pipelines across development, staging, and production
  • Partner with data scientists and applied AI engineers to take prototypes into production, including system design for net-new services
  • Own production reliability for AI services: monitoring, alerting, debugging, performance, and cost
  • Spot repeated patterns and turn them into reusable templates, so the team can ship its second and third variant of something without rebuilding it

What You'll Need

  • Six or more years in infrastructure, DevOps, platform, or ML engineering, with ownership of systems running in production
  • Deep hands-on experience across a wide range of AWS services, including compute, networking, storage, deployment, and monitoring
  • Infrastructure-as-code experience (Terraform, CDK, or CloudFormation)
  • Experience with containers and modern deployment patterns (Docker required, Kubernetes or ECS/EKS a plus), applied to CI/CD pipelines you've designed and operated for production services
  • Experience with orchestration and workflow tooling (Airflow, Dagster, Argo, Step Functions, or similar)
  • Comfort working through ambiguity and collaborating directly with data scientists and researchers

It Would Be a Bonus If You Had

  • Experience with ML platform components and data pipeline orchestration at scale
  • Experience running LLM-based or retrieval-based systems in production
  • Experience operating specialized data stores, including graph databases
  • Experience building internal tooling, templates, or reference implementations that other engineers adopted

Onsite Collaboration Requirement:
This role requires working onsite on Tuesday and Wednesday, with Thursday strongly encouraged as part of our company’s in-person collaboration model.

Why Join Us

Join us and help shape the future of education by turning cutting-edge AI into reliable product capabilities.

At Instructure, we're on a mission to help educators and students learn together, anytime, anywhere, and however works best. You'll join our research-driven team tackling education's biggest challenges with cutting-edge technology.

We value diversity, creativity, and passion, and invest in our teams through mentorship, hack weeks, internal conferences, and a culture where innovation thrives. Here, you'll have the chance to build the next generation of LMS features that make a real impact on students and teachers, and do it in a collaborative, supportive environment that encourages experimentation and growth.

Get in on all the awesome at Instructure!
We offer competitive, meaningful benefits in every country where we operate. While they vary by location, here's a general idea of what you can expect:

  • Competitive compensation, plus all full-time employees participate in our ownership program - because everyone should have a stake in our success.
  • Flexible work culture. Our remote, hybrid and in-office collaboration spaces vary by role, team and location.
  • Generous time off, including local holidays and our annual “Dim the Lights” period in late December, when teams are encouraged to step back and recharge based on departmental needs.
  • Comprehensive wellness programs and mental health support
  • Learning and development resources, including professional development tools and tuition reimbursement, to support your growth
  • The technology and tools you need to do your best work
  • Motivosity employee recognition program
  • A culture rooted in inclusivity, support, and meaningful connection

We believe in hiring great people and treating them right. The more diverse we are, the better our ideas and outcomes.

Instructure is an Equal Opportunity Employer. We comply with applicable employment and anti-discrimination laws in every country where we operate.

All employees must pass a background check as part of the hiring process. To help protect our teams and systems, we’ve implemented identity verification measures. Candidates may be asked to verify their legal name, current physical location, and provide a valid contact number and residential address, in accordance with local data privacy laws.

Any attempt to misrepresent personal or professional information will result in disqualification.

This is a saved copy of a posting published elsewhere. Postings get taken down without notice — check the employer's site before applying. mentors.coach is not the hiring party.

Cloud Engineer

Senior DevOps Engineer with Golang (f/m/x)

Sii Poland

Remote

Apply on the employer's site

Role description

We are looking for a skilled Senior DevOps Engineer to join a project focused on enhancing and modernizing client's cloud platform. This role offers the flexibility of remote work, allowing you to contribute to significant improvements in cloud infrastructure and automation processes. If you are passionate about cloud technologies and automation, this opportunity may be the right fit for you.

Your tasks

  • Building and maintaining platform integrations and automation workflows
  • Developing solutions using Go/Golang to enhance cloud operations
  • Implementing Infrastructure as Code using Terraform
  • Integrating cloud APIs for VMware, Azure, and AWS platforms
  • Creating and managing CI/CD pipelines to streamline deployments
  • Utilizing PowerShell and Bash scripting for automation
  • Managing Kubernetes and container platforms for efficient application deployment
  • Applying configuration management tools like Ansible to maintain system integrity

Requirements

  • Minimum 5 years of experience in DevOps or cloud engineering
  • Hands-on mastery of Go/Golang development
  • Experience with VMware and cloud API integrations
  • Knowledge of AWS or Azure services
  • Advanced level of English

Nice to have

  • Practical experience in Azure and/or AWS platform engineering
  • Familiarity with Ansible or similar configuration management tools
  • Strong command of Terraform and Infrastructure as Code principles
  • Familiarity with CI/CD platforms and automation pipelines
  • Experience with Kubernetes and container orchestration

Job no. JOB-R8PYA

Sii ensures that all hiring decisions are made solely on the basis of qualifications and competence. We are committed to equal and fair treatment of all, regardless of legally protected characteristics. At Sii, we promote a diverse and inclusive work environment, in full compliance with applicable anti-discrimination laws.

Benefits For You

  • Great Place to Work
  • Solid financial situation
  • Contracts with the biggest brands
  • Centre of internal trainings
  • Many experts you can learn from
  • Open and accessible management team
  • Profit sharing
  • Passion Sponsorship program
  • Regular integration events and trips
  • Comfortable and well-equipped offices
  • MySii app
  • Medical care

This is a saved copy of a posting published elsewhere. Postings get taken down without notice — check the employer's site before applying. mentors.coach is not the hiring party.

That is every opening in this category and country

Azure Data EngineerJobgether

Apply on the employer's site