EY - GDS Consulting - AI And DATA - GCP - Senior

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. 

The opportunity

We are seeking an experienced GCP Data Engineer with strong technology and data understanding in GCP engineering space, having proven delivery capability. The candidate will be responsible for building, maintaining, and optimizing data pipelines and data platforms on Google Cloud (Big Query). The role will focus on data ingestion, transformation, orchestration, automation, and analytics enablement for enterprise-scale solutions.

Your Technical responsibilities:

• Design and develop scalable ETL/ELT pipelines on GCP
• Build and maintain data ingestion and transformation frameworks using BigQuery and GCP services
• Develop Cloud Functions and automation scripts for data movement and processing
• Create and maintain workflows using Cloud Composer/Airflow
• Implement data reconciliation, validation, and data quality controls
• Troubleshoot pipeline failures and performance issues using monitoring and logging tools
• Support migration of on-premises or legacy workloads to GCP
• Create dashboards, reports, and analytics solutions for business users
• Collaborate with business, architecture, and development teams to deliver data-driven solutions.
• Use Data flow or STS to build pipeline from traditional and cloud source to GCP.
• Good understanding of cloud design considerations and FinOps 
• Proficient in a modern scripting language like Python, Spark and Scala.
• Work with container technology such as Docker, version control systems (Github), build management and CI/CD tools (Concourse, Jenkins)
• Data Pipeline Workflows: Build and maintain data pipelines using tools and services like Dataflow, Dataproc, Apache Beam, Apache Airflow, Cloud Composer, etc. to collect, process, and distribute data.
• CI/CD Implementation: Implement CI/CD pipelines for data applications using services like Cloud Build, Jenkins, or Gitlab. Continuous testing, continuous integration, build, package, and deployment should be automated across multi-cloud environments.
• Code Management: Take charge of source code repositories like GitHub or Bitbucket, ensuring robust version control practices.
• Data Security & Compliance: Implement security best practices. Handle actions such as encryption, managing and securing service accounts, secret management (like with Secret Manager), authentication, access control, and data compliance necessities (like GDPR).
• Performance Optimization and Cost Control: Monitor, debug, troubleshoot, and optimize performance of Dataflow jobs, and other data infrastructure. Implement strategies for optimizing cost across multiple clouds.
• Data Lakes and Data Warehouses Management: Manage BigQuery or other cloud data warehouse solutions and services for Data Lakes.

Mandatory Requirements (Qualifications)

We are looking for the candidates with the following: 

• BE/BTech/MCA with a sound industry experience of 5 to 8 years
• 3–6+ years of Data Engineering experience with hands-on GCP implementation
• Programming Language- Python, SQL, Spark (PySpark)
• Experience in FS domain- preferably asset wealth management
• Experience with CI/CD pipelines and cloud-native development practices.
• Exposure to Apache Spark, Databricks, and modern data engineering frameworks.
• Strong communication skills
• Google Cloud Certified is add-on

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