Join EY and embark on a career path as unique as you are. Leverage our global scale, supportive environment, inclusive culture, and cutting-edge technology to become your best self. Your distinct perspective is vital in helping EY achieve even greater success. Together, we can create an exceptional experience for you and foster a better working world for everyone.

Develop and manage robust data pipelines using tools such as Apache Kafka, Apache Spark, or AWS Glue for efficient data ingestion, processing, and transformation. Design and implement scalable data models within data warehouses like Amazon Redshift or Google BigQuery, and data lakes such as AWS S3 or Azure Data Lake to support advanced analytics. Collaborate closely with data scientists and analysts to ensure data availability and accessibility for critical insights.

Automate data processes through ETL frameworks like Apache NiFi, Talend, or custom Python scripts, maintaining high data quality. Optimize data pipeline performance with tools like Apache Airflow or AWS Step Functions, adhering to best practices in data processing and workflow management. Write, test, and maintain scripts in Python, SQL, or Bash for data manipulation, automation, and validation.

Implement CI/CD practices for data engineering workflows using Jenkins, GitLab CI, or Azure DevOps to automate deployment. Integrate data solutions into existing infrastructure with DevOps teams, utilizing Infrastructure as Code (IaC) tools like Terraform or AWS CloudFormation. Manage containerized data applications with Docker and orchestrate them using Kubernetes for enhanced scalability and reliability.

Establish monitoring and logging solutions with Prometheus, Grafana, or ELK Stack to track performance, troubleshoot issues, and ensure data integrity. Uphold data governance, security standards, and privacy regulations by embedding DevSecOps principles. Participate in code reviews to enhance data engineering best practices and contribute to the development of DevOps methodologies. Mentor junior engineers, guiding them on data architecture and tools. Document data architecture, processes, and workflows for knowledge sharing and onboarding. Utilize strong communication skills to foster effective collaboration across data science, analytics, and business teams.

We are seeking a seasoned DevOps Engineer with over 5 years of comprehensive Cloud and DevOps experience, including demonstrated leadership. A Bachelor's or Master's degree in Computer Science is required.

Expertise in Terraform and extensive experience across at least two major cloud platforms (AWS, Azure, GCP) are essential. Strong proficiency with Kubernetes, Helm charts, and designing/optimizing CI/CD pipelines (e.g., Jenkins, GitLab CI) is a must. Proficiency in Python and scripting languages such as Bash or PowerShell is also required.

Valued experience includes leading cloud migration projects, contributing to RFP/RFI processes, and mentoring teams. Exceptional problem-solving, communication, and collaboration abilities are critical. Experience with configuration management tools (Ansible, Puppet) and a solid understanding of DevSecOps principles are necessary. Experience with OpenShift is considered a significant advantage.