Data Developer
This role is eligible for our hybrid work model: Two days in-office.
Why this jobs a big deal
As a Data Developer in the Product Operating Model (POM), your focus is on bridging the gap between data engineering and operational excellence. You are accountable for building and maintaining the CI/CD pipelines, automation tools, and infrastructure that ensure our data systems are reliable, scalable, and high-performing. You will collaborate closely with Data Architects, Product Managers, and Engineering teams to optimize the delivery and lifecycle of trusted data solutions.
In this role, you will get to
1. Automation & CI/CD Practices
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Design, build, and optimize CI/CD pipelines and deployment workflows for data and AI/ML platforms.
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Develop and maintain internal tooling and self-service frameworks to improve developer productivity for data and AI/ML workloads.
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Implement GitOps-based workflows to manage infrastructure and application deployments.
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Continuously analyze and improve existing CI/CD processes with a focus on reliability, scalability, and operational excellence.
2. Infrastructure & Platform Engineering
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Design, implement, and support scalable cloud infrastructure primarily within the GCP ecosystem.
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Support containerized and microservice-based platforms using Kubernetes, Helm, and Docker.
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Manage declarative infrastructure-as-code (IaC) systems using Terraform.
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Ensure scalability, reliability, and performance of data and AI/ML platforms across cloud environments (GCP preferred, AWS is a plus).
3. Data Quality & Reliability
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Implement and maintain logging, alerting, and monitoring solutions using tools such as Splunk, Cloud Logging, and New Relic.
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Monitor, troubleshoot, and resolve production issues, including participating in incident response and root-cause analysis.
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Build automation and operational improvements to enhance platform reliability, scalability, and developer experience.
4. Collaboration & Governance
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Partner with Data Architects, Data Engineers, ML/AI teams, and Infrastructure teams to align infrastructure with enterprise standards and governance policies.
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Facilitate collaboration between Data and AI/ML engineering and operations teams to ensure smooth delivery and release readiness.
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Embed security, privacy, and operational best practices into infrastructure and deployment workflows.
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Participate in infrastructure design discussions, technical planning, and risk assessments.
Who you are
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The Operational Driver: You are the engine that ensures data and AI/ML teams have the automated tools and stable environments they need to deliver actionable data.
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A Technical Bridge: You bridge the gap between software engineering best practices, cloud infrastructure, and data platform requirements.
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A Guardian of Excellence: You are responsible for the reliability, security, scalability, and sustainability of the systems that power critical business and analytics platforms.
Qualifications
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Bachelor’s degree in Computer Science or a related field.
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3–5+ years of hands-on experience in DevOps, Cloud Engineering, Platform Engineering, or related fields.
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Strong understanding of DevOps principles, CI/CD practices, and automation frameworks.
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Hands-on experience with cloud platforms such as GCP, AWS, or Azure.
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Familiarity with cloud-native data, compute, storage, and IAM services across major cloud providers.
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Experience with orchestration and workflow management tools such as Airflow or equivalent platforms.
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Experience with Infrastructure as Code tools such as Terraform.
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Strong experience with container orchestration platforms including Kubernetes and Helm.
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Exposure to CI/CD and deployment tools such as GitHub Actions.
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Experience with monitoring and observability platforms such as Splunk, Cloud Logging, and New Relic.
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Proficiency in scripting languages such as Python and bash/shell scripting.
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Familiarity with databases such as MySQL, MongoDB, Redis, or Couchbase is a plus.
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Experience working with Agile tools such as Jira.
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Good troubleshooting, collaboration, and documentation skills.
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Illustrated history of living the values necessary to Priceline: Customer, Innovation, Team, Accountability and Trust.
There are a variety of factors that go into determining a salary range, including but not limited to external market benchmark data, geographic location, and years of experience sought/required. In addition to a competitive base salary, certain roles may be eligible for an annual bonus and/or equity grant.
The salary range for this position is $100,000-120,000 CAD.