Data Engineering, Cloud Migration & Platforms Engineer

Job Description

AI Disclosure: As part of the application process Artificial Intelligence will be used in the hiring process for this role

This role is categorized as hybrid. This means the successful candidate is expected to report to the Markham Elevation Centre or the Oshawa Elevation Centre at least three times per week.

The Team &Opportunity

The Enterprise Data team is responsible for supporting and modernizing the data platforms that enable analytics artificial intelligence customer engagement strategic planning and other enterprise capabilities across GM.

We are building a new team to support the existinglegacyenvironment while migrating and transforming the architecture to a cloud-based platform. This role will help establish the engineering standards reusable platform capabilities delivery automation and operational practices required for a secure scalable governed and reliable cloud data ecosystem.

The ideal candidate combines strong data engineering fundamentals with cloud platform engineering automation and production operations. They are comfortable working across architecture development infrastructure security quality engineering and incident response to deliver sustainable data products and services.

The Role

As a Data Engineering Cloud Migration & Platforms Engineer you will design build migrate automate and support data platforms and pipelines across on-premises and cloud environments. You will contribute to the modernization of Oracle-based enterprise data workloads develop cloud-native data solutions and help create the engineering foundation for governed analytics and AI.

This role combines data engineering and platform engineering responsibilities including data pipeline development cloud infrastructure as code CI/CD environment promotion security and access controls observability reliability engineering testing documentation and operational support. The specific cloud implementation may be Azure Google Cloud Platform or a multi-cloud architecture depending on platform direction and business requirements.

Key Responsibilities

• Assess existing Oracle-based data architecture workloads dependencies interfaces data flows and operational processes to support migration planning and execution.

• Design and implement scalable data pipelines for batch and near-real-time processing including ingestion transformation validation reconciliation and publishing.

• Develop migration patterns for data schemas ETL/ELT workloads stored procedures interfaces and downstream consumers while maintaining data quality and business continuity.

• Build and maintain cloud data-platform capabilities using services such as Azure Data Lake Storage Gen2 Azure Databricks Azure Kubernetes Service or comparable Google Cloud services such as Cloud Storage Dataproc BigQuery GKE and Pub/Sub.

• Use Databricks capabilities including Workflows Unity Catalog Delta Lake MLflow and Asset Bundles where appropriate to support governed data engineering and AI/ML workloads.

• Develop reusable infrastructure as code using Terraform including cloud networking data-platform and Databricks resources; manage remote state and reusable modules.

• Design and support CI/CD workflows for data pipelines infrastructure configuration and platform components using GitHub Actions Azure Pipelines or comparable cloud-native tooling.

• Automate deployment and environment promotion across development test staging and production environments.

• Implement data security identity access management encryption secrets management key rotation and least-privilege controls in alignment with GM policies and cloud best practices.

• Establish data governance practices including cataloging lineage classification access controls retention auditability and responsible use of enterprise data.

• Design and maintain monitoring logging alerting data-quality checks and operational dashboards that provide clear visibility into pipeline platform and service health.

• Improve reliability scalability performance and cost efficiency through automation resilient design capacity planning and continuous optimization.

• Lead or support incident response service recovery root cause analysis and post-incident reviews for data-platform and pipeline issues.

• Define and support operational targets such as SLAs SLOs freshness objectives recovery objectives and error-budget-aware practices.

• Develop automated unit integration data-quality regression and end-to-end tests for pipelines and platform components.

• Collaborate with data architects application teams analytics and AI practitioners security partners product owners and global technology teams to translate requirements into reliable data solutions.

• Participate in two-week sprints and contribute to backlog refinement estimation delivery planning demos and continuous improvement.

• Create and maintain architecture diagrams data-flow documentation API and interface documentation runbooks onboarding guides README files and production-readiness materials using tools such as Confluence Lucidchart and Jira.

Required Qualifications and Skills

• Bachelors degree in Computer Science Engineering Information Systems Data Engineering or a related discipline or equivalent practical experience.

• At least 3 years of professional experience in data engineering cloud platform engineering DevOps software engineering or a related field with demonstrated experience delivering production data solutions.

• Hands-on experience designing and supporting data pipelines and ETL/ELT workloads preferably involving Oracle or another enterprise relational database platform.

• Strong Python experience for automation developer tooling data engineering and PySpark-based processing.

• Experience with SQL relational data modeling schema design query optimization and data reconciliation.

• Experience with at least one major cloud platform preferably Azure or Google Cloud Platform and the ability to learn or support the other.

• Experience with infrastructure as code using Terraform including reusable modules remote state and environment-specific configuration.

• Experience with Git branching strategies pull requests code reviews and automated CI/CD practices.

• Experience with a cloud data platform or lakehouse technology such as Databricks Delta Lake BigQuery Synapse or an equivalent platform.

• Understanding of cloud networking identity and access management encryption secrets management and secure service-to-service integration.

• Experience implementing monitoring logging alerting operational dashboards and data-quality controls.

• Strong troubleshooting analytical communication and cross-functional collaboration skills.

Preferred Qualifications

• Experience migrating Oracle databases ETL jobs stored procedures or data warehouses to Azure Google Cloud Platform Databricks BigQuery or equivalent cloud services.

• Strong hands-on experience with Databricks Workflows Unity Catalog Delta Lake MLflow and Asset Bundles.

• Azure experience with ADLS Gen2 Key Vault Entra ID AKS Azure networking and Azure DevOps or GitHub Actions.

• Google Cloud experience with Cloud Storage BigQuery Dataproc GKE Pub/Sub Secret Manager Cloud IAM and VPC networking.

• Experience with streaming and event-driven data processing using Apache Kafka Apache Pulsar Pub/Sub or an equivalent technology.

• Experience with Kubernetes Azure Container Apps GKE or other containerized runtime environments.

• Experience with Datadog or another observability platform.

• Familiarity with MLflow model or feature pipelines experiment tracking and production monitoring for AI/ML workloads.

• Experience with HashiCorp Vault or comparable enterprise secrets-management tools.

• Experience working in regulated security-sensitive or enterprise-scale environments.

• Experience with production readiness reviews incident management postmortems and service reliability practices.

Compensation:

The salary range for this role is $97800 to $146600. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.

GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP NOW OR IN THE FUTURE.

About GM

Our vision is a world with Zero Crashes Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day individually and collectively to drive meaningful change through our words our deeds and our culture. Every day we want every employee to feel they belong to one General Motors team.

Non-Discrimination and Equal Employment Opportunities

General Motors is committed to being a workplace that is not only free of unlawful discrimination but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required where applicable to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more visit How we Hire.

Accommodations

General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment email us or call your email please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.