Join EY's Cloud Engineering team as a Senior Data Platform Engineer and contribute to global IT project delivery. You'll be instrumental in building a career that's as unique as you are, leveraging EY's global scale, supportive culture, and advanced technology to achieve your full potential. Your unique perspective is vital in helping EY excel.

This role offers the opportunity to make a significant impact, driving innovation and excellence in data platform solutions. Become part of a dynamic team that shapes the future of technology for clients worldwide.

Architect and manage scalable, secure, and cost-effective Databricks/Snowflake infrastructure on Azure and AWS. Establish robust data governance frameworks, including access controls, lineage, and compliance. Design and implement DataOps and MLOps pipelines for automated data workflows. Automate infrastructure provisioning using IaC tools like Terraform, ARM, or Bicep. Integrate Databricks/Snowflake with enterprise CI/CD pipelines for lifecycle management. Implement comprehensive monitoring, logging, and alerting for Databricks workloads. Optimize Databricks cluster performance and cost efficiency. Ensure adherence to security best practices, including encryption and compliance. Collaborate with data engineering, analytics, and ML teams to streamline workflows. Drive adoption of DevSecOps practices within data pipelines. Lead incident response and root cause analysis for platform issues. Document architecture, processes, and best practices for knowledge sharing.

A Bachelor's degree in BE/B.Tech/MCA coupled with 4-8 years of extensive industry experience is required.

Essential skills include strong knowledge of cloud computing environments (Azure, AWS), with hands-on experience in Databricks administration on these platforms. Proficiency in DevOps practices, including setting up CI/CD pipelines using Azure DevOps, GitHub Actions, or GitLab CI, is crucial.

You must possess a deep understanding of DataOps and MLOps principles, covering orchestration, monitoring, and governance. Hands-on experience with containerization technologies such as Docker and Kubernetes (AKS/EKS/GKE) is necessary. Proficiency in scripting languages like PowerShell, Python, Groovy, and Shell Scripting, along with cloud-native CLIs, is essential.

Expertise in Infrastructure as Code (IaC) tools like Terraform or ARM/Bicep, and configuration management tools such as Ansible, Chef, or Puppet, is mandatory. A strong ability to create Golden Paths for end-to-end developer workflows is also a key requirement.