Stryker—Senior Engineer, EDT Data & Analytics Cloud Engineering

Job description

Description: Work Flexibility: Hybrid Senior Engineer, EDT Data & Analytics Cloud Engineering The Senior Cloud Platform Engineer supports the operational excellence, security, and reliability of the enterprise data & analytics platform on Azure. The role combines platform operations, DevOps automation, and Infrastructure as Code across the core stack - Azure Databricks, Synapse, ADLS Gen2, Azure SQL, Azure Data Factory, Key Vault, and Unity Catalog - with a reliability-engineering mindset: automate repeatable work, apply security best practices by default, and help keep the platform highly available for global data engineering and analytics teams. What you will do: ​​DevOps Pipeline Management & CI/CD - Build and maintain Azure DevOps pipelines for CI/CD, automating build, test, and deployment across development, testing, and production environments. - Support high service availability through solid workflow management, smooth promotion processes, and efficient pipeline operations. Infrastructure as Code & Environment Provisioning ​ - Implement and maintain platform infrastructure as code using Terraform, ensuring consistent, repeatable provisioning and configuration across environments. - Provision and maintain environments — workspaces, compute, storage, networking, and access — using automated IaC processes, and help identify configuration drift. Platform Security & Access Management - Support platform security alongside development and operations teams — implementing RBAC, access controls, and security configurations across Azure Data Factory, Databricks, Synapse, Azure SQL, ADLS Gen2, Key Vault, and Unity Catalog. - Apply Azure data service security best practices, including secrets management, identity integration, and least-privilege access. Platform Operations & Reliability Engineering - Contribute to platform monitoring, alerting, performance tuning, and incident response, with a focus on root-cause analysis and preventive fixes. - Monitor integration runtimes and platform services, troubleshooting pipeline and runtime issues to help protect SLAs. Data Engineering Operations - Partner with Data Platform and Data Product teams to build and operationalize data pipelines, orchestration, and Databricks workloads. What you need: - Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, Business, or a related technical field, with 2-5 years of experience in cloud engineering, data warehousing, or modern data & analytics platforms. - Strong hands-on expertise with Azure data technologies, including Azure Databricks, Synapse Analytics, ADLS Gen2, Azure SQL, Azure Data Factory, Key Vault, and Unity Catalog. - Proven experience implementing Azure platform security, governance, and data service best practices to deliver secure, scalable, and reliable cloud solutions. - Proficiency in Azure DevOps and CI/CD pipeline management, with experience automating deployments and releases across multiple environments. - Working knowledge of Infrastructure as Code (IaC) using Terraform to provision, manage, and standardize cloud infrastructure. - Experience monitoring and optimizing cloud data platforms, including alerting, performance tuning, incident management, and root cause analysis. - Strong analytical, troubleshooting, and problem-solving capabilities, with the ability to identify patterns, resolve complex technical issues, and drive continuous improvement. - Excellent communication and collaboration skills, with a proactive mindset for ownership, automation, and process optimization while partnering effectively across engineering, operations, security, and business teams. - Cloud Engineering certifications on Azure/Databricks platform is a plus. Travel Percentage: None