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General Motors
General Motors
Sponsor pentru viza H1BIndustria autoIndustria prelucrătoareTransport
General Motors este o companie globală din industria auto și de producție, care activează în domeniile ingineriei vehiculelor, producției, transporturilor și tehnologiei informației. Fondată în 1908, GM dezvoltă tehnologii menite să avanseze mobilitatea, urmărindu-și în același timp viziunea de zero accidente, zero emisii și zero congestie. Operațiunile sale internaționale reunesc echipe numeroase și multidisciplinare, axate pe inovare, transport sustenabil și viitorul industriei auto.
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Locurile de muncă ale companiei

Data Engineering, Cloud Migration and Platforms Engineer - General Motors (Hybrid)

Modernize General Motors’ Oracle workloads through cloud migration and platform engineering. Build secure, governed data platforms, pipelines, infrastructure automation, and reliable operating practices.

CACanada
97.800 $ – 146.600 $ / an
HibridNormă întreagăNivel mediuSeniorLimbă Obligatorie: englezăInginer cloud
ApacheAzureBigQueryCloudETLGoogle Cloud PlatformKafkaKubernetesOraclePulsarPySparkPythonSQLTerraformUnityVault

Descriere

  • Evaluate Oracle-based architectures, workloads, dependencies, interfaces, data flows, and operating processes to plan and execute migrations.
  • Create scalable batch and near-real-time pipelines for data ingestion, transformation, validation, reconciliation, and publishing.
  • Develop migration approaches for data, schemas, ETL/ELT workloads, stored procedures, interfaces, and downstream consumers.
  • Build and operate cloud data-platform capabilities across Azure, Google Cloud Platform, and multi-cloud environments.
  • Apply Databricks Workflows, Unity Catalog, Delta Lake, MLflow, and Asset Bundles when appropriate.
  • Create reusable Terraform infrastructure as code for cloud, networking, data-platform, and Databricks resources.
  • Design CI/CD workflows and automate deployments and environment promotion across development, test, staging, and production.
  • Apply data-security controls covering identity and access management, encryption, secrets, key rotation, and least privilege.
  • Establish governance practices for cataloging, lineage, classification, retention, auditability, and responsible data use.
  • Implement monitoring, logging, alerting, data-quality checks, and operational dashboards.
  • Increase platform reliability, scalability, performance, and cost efficiency through automation and ongoing optimization.
  • Lead or assist with incident response, service restoration, root cause analysis, and post-incident reviews.
  • Define and support SLAs, SLOs, data-freshness targets, recovery objectives, and error-budget practices.
  • Build automated unit, integration, data-quality, regression, and end-to-end testing.
  • Work with architects, application teams, analytics and AI practitioners, security partners, product owners, and global technology teams.
  • Contribute to two-week sprints, backlog refinement, estimation, delivery planning, demonstrations, and continuous improvement.
  • Maintain architecture diagrams, data-flow records, API and interface documentation, runbooks, onboarding guides, README files, and production-readiness materials.

Cerințe

  • Bachelor’s degree in computer science, engineering, information systems, data engineering, or a related field, or equivalent practical experience.
  • At least three years of professional experience in data engineering, cloud platform engineering, DevOps, software engineering, or a related discipline.
  • Proven experience delivering production-grade data solutions.
  • Practical experience designing and supporting data pipelines and ETL/ELT workloads, ideally with Oracle or another enterprise relational database.
  • Strong Python skills for automation, developer tooling, data engineering, and PySpark processing.
  • Experience with SQL, relational modeling, schema design, query optimization, and data reconciliation.
  • Experience with at least one major cloud platform, preferably Azure or Google Cloud Platform.
  • Experience building infrastructure as code with Terraform, including reusable modules, remote state, and environment-specific configuration.
  • Experience using Git, branching strategies, pull requests, code reviews, and automated CI/CD workflows.
  • Experience with a cloud data platform or lakehouse such as Databricks, Delta Lake, BigQuery, Synapse, or an equivalent technology.
  • Knowledge 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 abilities.
  • Preferred: experience migrating Oracle databases, ETL jobs, stored procedures, or data warehouses to cloud services.
  • Preferred: hands-on experience with Databricks Workflows, Unity Catalog, Delta Lake, MLflow, and Asset Bundles.
  • Preferred: familiarity with Azure services such as ADLS Gen2, Key Vault, Entra ID, AKS, Azure networking, and Azure DevOps or GitHub Actions.
  • Preferred: familiarity with Google Cloud services such as Cloud Storage, BigQuery, Dataproc, GKE, Pub/Sub, Secret Manager, Cloud IAM, and VPC networking.
  • Preferred: experience with streaming and event-driven processing using Apache Kafka, Apache Pulsar, Pub/Sub, or equivalent technologies.
  • Preferred: experience with Kubernetes, Azure Container Apps, GKE, or other containerized runtimes.
  • Preferred: experience with Datadog or another observability platform.
  • Preferred: experience with MLflow, model or feature pipelines, experiment tracking, and production monitoring for AI/ML workloads.
  • Preferred: experience with HashiCorp Vault or comparable enterprise secrets-management tools.
  • Preferred: experience in regulated, security-sensitive, or enterprise-scale environments.
  • Preferred: experience with production-readiness reviews, incident management, postmortems, and service-reliability practices.
  • Must not require GM immigration-related sponsorship now or in the future.

Beneficii

  • Hybrid work arrangement.
  • Work involving cloud data platforms, analytics, artificial intelligence, and enterprise modernization.
  • Inclusive workplace focused on belonging and professional development.
  • Information provided about role-related assessments and/or pre-employment screening.
  • Accommodation support is available for applicants with disabilities.

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