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Software Engineer, Infrastructure

Remote (EST timezone) • Remote • Full-time Contract • Req ID: GDBI-0T2V4Q8S

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Software Engineer, Infrastructure

Location: Remote (EST preferred) • Type: Full-time • Status: Open
About Global Data and BI Global Data and BI is hiring on a rolling basis for Data, BI & Analytics and ML/AI projects for large corporations. Beyond consulting services, we build production-ready business platforms and SaaS applications that leverage modern cloud technologies, data analytics, and AI capabilities. We deliver enterprise-grade solutions with certified engineers in AWS and Microsoft Azure / Power BI technologies. Our focus includes transformation projects in the financial industry, custom platform development, and our proprietary Noème suite of products. Our mission is to transform the corporate data journey from complexity to strategic clarity, ensuring data is not just collected, but leveraged to drive smarter decisions, stronger businesses, and lasting impact.

Summary

The Infrastructure team builds and maintains the foundational systems that power Global Data and BI's data platforms, Noème products, and client solutions. This includes orchestration platforms for data pipelines, cloud infrastructure automation, configuration management, observability systems, and the core services that ensure our data platforms are reliable, scalable, and secure for enterprise clients.

As part of the Infrastructure Team, you'll have the opportunity to shape how Global Data and BI manages and scales its data platform infrastructure, enabling data engineers and product teams to build and deploy solutions confidently while ensuring high availability and performance for our clients.

What you'll do (roles & responsibilities)

  • Build and maintain orchestration infrastructure for data pipelines including workflow scheduling, task execution, dependency management, and monitoring systems
  • Develop cloud infrastructure automation using Infrastructure as Code (Terraform, Pulumi, CloudFormation, ARM templates) for AWS and Azure environments
  • Implement configuration management platforms that enable safe, version-controlled infrastructure and application configuration across environments
  • Design and maintain Kubernetes infrastructure for containerized workloads including data processing jobs, APIs, and microservices
  • Build CI/CD pipelines for infrastructure deployments, ensuring reliable and repeatable infrastructure provisioning
  • Develop observability and monitoring systems to track infrastructure health, performance metrics, and operational insights
  • Support data pipeline orchestration platforms (Apache Airflow, Dagster, Prefect) ensuring reliability and scalability for data engineering teams
  • Implement security and compliance controls for cloud infrastructure including network security, encryption, access management, and audit logging
  • Optimize infrastructure costs by implementing resource tagging, right-sizing, auto-scaling, and cost monitoring
  • Build self-service infrastructure tools that enable engineering teams to provision and manage infrastructure independently
  • Maintain high availability systems through redundancy, failover mechanisms, disaster recovery planning, and chaos engineering practices
  • Debug production infrastructure issues with minimal disruption, whether replacing components, managing failovers, or responding to incidents
  • Participate in on-call rotation responding to infrastructure incidents to uphold service reliability and quickly restore normal operations
  • Partner with data engineering and product teams to ensure infrastructure aligns with evolving business needs and technical requirements
  • Evaluate and integrate new technologies to keep infrastructure modern and address emerging challenges
  • Document infrastructure architecture including diagrams, runbooks, and operational procedures
  • Implement infrastructure testing including integration tests, chaos experiments, and disaster recovery drills
  • Support multi-cloud and hybrid cloud architectures across AWS and Azure
  • Build infrastructure for AI/ML workloads including GPU compute, model serving, and training pipelines
  • Contribute to infrastructure standards and best practices across the organization

What you should have (Must-Haves)

  • Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience
  • 2-5 years of software engineering or infrastructure engineering experience
  • Strong programming skills in languages like Python, Go, or Java for building infrastructure tools and automation
  • Experience with cloud platforms (AWS and/or Azure) and understanding of core cloud services (compute, storage, networking, databases)
  • Understanding of distributed systems and ability to design solutions that account for tradeoffs like consistency, latency, and scalability
  • Experience with Infrastructure as Code using Terraform, Pulumi, CloudFormation, or similar tools
  • Knowledge of containerization and experience with Docker and container orchestration
  • Understanding of CI/CD principles and experience building deployment pipelines
  • Familiarity with Linux/Unix systems and command-line tools
  • Experience with version control (Git) and collaborative development workflows
  • Strong problem-solving abilities and debugging skills for complex infrastructure issues
  • Pragmatic and business-oriented - understanding the balance between craft, speed, and long-term maintainability
  • Ownership mindset - comfortable taking ownership of ambiguous problems and driving solutions independently
  • Systems thinking - ability to understand how components interact and design holistic solutions
  • Customer empathy - focus on enabling other engineers and supporting them in building reliable systems
  • Adaptable and fast-paced - thrive in unstructured environments with rapidly changing requirements

Nice-to-Haves

  • Experience with Kubernetes and container orchestration in production environments
  • Knowledge of data orchestration platforms (Apache Airflow, Dagster, Prefect, Azure Data Factory)
  • Experience with monitoring and observability tools (Prometheus, Grafana, DataDog, New Relic, CloudWatch)
  • Understanding of networking including VPCs, subnets, load balancers, DNS, and security groups
  • Experience with database administration for PostgreSQL, MySQL, MongoDB, or other databases
  • Knowledge of message queues (Kafka, RabbitMQ, SQS, Event Hubs) and event-driven architectures
  • Familiarity with service mesh technologies (Istio, Linkerd) for microservices
  • Experience with configuration management tools (Ansible, Chef, Puppet, Salt)
  • Understanding of security best practices for cloud infrastructure and compliance frameworks (SOC 2, ISO 27001)
  • Experience with disaster recovery and business continuity planning
  • Knowledge of cost optimization strategies for cloud infrastructure
  • Experience with data platform infrastructure specific to data warehouses, data lakes, or lakehouse architectures
  • Familiarity with streaming data infrastructure (Kafka, Kinesis, Event Hubs)
  • Experience with GPU infrastructure for AI/ML workloads
  • Understanding of FinOps practices and cloud cost management
  • Background in SRE practices including SLOs, SLIs, error budgets
  • Experience with multi-cloud deployments and hybrid cloud architectures
  • Certifications in AWS or Azure (Solutions Architect, DevOps Engineer, or similar)
  • Contributions to open source infrastructure projects
  • Bilingual proficiency in English and French (asset for supporting bilingual engineering teams)

Work details

  • Location: Remote (EST timezone preferred for collaboration with engineering and operations teams)
  • Reporting relationship: You will report to the Engineering Manager for Infrastructure, Director of Infrastructure, or Director of Platform Engineering

Compensation

Competitive salary package adjusted to your local market and country of residence. Compensation is location-based and reflects regional market standards. We benchmark against leading technology companies in your country to ensure competitive, fair pay for mid-level infrastructure engineers with cloud and platform engineering expertise.

Our commitment to diversity, equity, and inclusion We're committed to employment equity and encourage women, Indigenous Peoples, persons with disabilities, veterans and persons of all races, ethnicities, religions, abilities, sexual orientations, and gender identities and expressions to apply. We also welcome applications from Latin America countries, as the position is remote.

What happens after you apply

Timeline: We aim to complete our process within 2-3 weeks of application.

Step 1
Apply Submit your application. If you applied before and were not successful, you are welcome to apply again.
Step 2
Initial call (1 hour) If pre-selected, we schedule an initial conversation.
Step 3
Technical interview (1h30) If shortlisted, covering infrastructure, distributed systems, and cloud architecture.
Step 4
Practical exercise Take-home or pair programming exercise designing or implementing infrastructure solution.
Step 5
Panel interview (1h30) Meet with Infrastructure and Platform Engineering teams.
Step 6
Hiring decision If selected, we send an offer and next steps, otherwise we inform you by email.
If you don't hear back from us after application or any interview stage, it means we do not pursue your application.
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