Join EY's Digital Engineering team as a GCP Cloud AI & Data Engineer and contribute to the forefront of cloud-native data solutions, particularly leveraging Java and GCP technologies. This role offers a unique opportunity to be part of a leading professional services organization with a dedicated focus on the financial services marketplace, working within multi-disciplinary global teams. You'll play an instrumental role in the growth of a new service offering, advising clients on critical digital transformation initiatives.

EY Digital Engineering is a specialized business unit focused on leveraging deep industry experience and strong functional capabilities. We help clients analyze, design, and implement digital transformation strategies, addressing pressing challenges in business strategy, customer engagement, profit optimization, innovation, and technology. Our team excels at translating strategy into actionable technical designs and transformation plans, enabling clients to maintain competitive advantage in a rapidly changing landscape.

Design, build, and optimize robust cloud-native data pipelines and ETL workflows using languages such as Python, Java, Go, or Scala, with a preference for running on Flink, Spark, or Google Cloud Dataflow.

Develop and implement Cloud-native AI/ML solutions using Vertex AI for various industries, sharing relevant use cases.

Integrate Generative AI (GenAI) capabilities into data pipelines to enhance automation, insight generation, and predictive analytics.

Stay abreast of emerging AI technologies and proactively explore innovative ways to embed GenAI-driven intelligence into enterprise data platforms.

Manage the entire application and container lifecycle, including setting up CI/CD pipelines for build and deployment.

Handle issue escalation according to standard procedures and document technical knowledge effectively.

A Bachelor's degree in a relevant field (BE/B.Tech/MCA) is required, coupled with 4 to 6 years of sound industry experience.

Proficiency in building data pipelines and ETL workflows using Python, Java, Go, or Scala, with experience on platforms like Flink, Spark, or Google Cloud Dataflow.

Hands-on experience in building Cloud-native (AI)ML Solutions with Vertex AI, including sharing supporting use cases.

Experience integrating GenAI capabilities with data pipelines and a strong understanding of emerging AI technologies.

Expertise in public cloud environments, with a mandatory Professional or Practitioner certification on GCP.

Familiarity with the entire application and container lifecycle management, including CI/CD pipeline setup.

Excellent written and oral communication skills; presentation skills are a plus.

Adherence to Apache Beam and Java/SpringBoot is considered advantageous.