Join EY's Global Delivery Services (GDS) Consulting team as a Senior Snowflake Data Engineer. You'll leverage your expertise to help clients solve complex business challenges using data and technology. This role offers a unique opportunity to grow your career within a leading global firm and a dynamic Data and Analytics team, working on impactful projects across various industries including Banking, Insurance, Manufacturing, Healthcare, and Finance.

EY is committed to fostering a culture of growth, innovation, and inclusivity. We provide comprehensive support, coaching, and opportunities for skill development, allowing you to shape your career path and take on challenging assignments in an interdisciplinary environment. Experience the EY difference and contribute to building a better working world.

Develop and deploy robust big data pipelines utilizing Snowflake's cloud data warehousing capabilities. Design, develop, and migrate ETL processes from on-premise environments to cloud services. Collaborate with senior stakeholders to understand business objectives and contribute to workstream delivery. Optimize model code for enhanced execution speed and efficiency. Participate in all phases of the Big Data solution delivery lifecycle, including analysis, design, development, testing, deployment, and support.

A computer science graduate or equivalent with 4-7 years of industry experience is required. Proven hands-on experience as a developer in data warehousing and ETL is essential, with specific expertise in Snowflake development. Proficiency in Snowflake data modeling, including roles, schemas, databases, and security policies, is crucial. Experience with Snowflake tasks, streams, and stages, alongside data integration using third-party tools like DBT, is expected. Knowledge of DBT modeling and CDC handling, version control, and event-triggered or scheduled tasks is also necessary. While not mandatory, experience with Snowflake's advanced concepts such as resource monitors and performance tuning is a plus. Familiarity with developing data pipelines for batch and real-time analytics, handling large datasets, and data wrangling using SQL & NoSQL databases and programming languages like Python is also beneficial. Understanding of file formats (ORC, Parquet, AVRO) for optimization and compression, AIML and application integration workflows through Snowpark and SPCS, and data sharing across cloud data platforms are key. Knowledge of DevOps and containerization is advantageous, with deployment experience being a preference. Experience working in an Agile delivery methodology is preferred. A proactive, self-motivated work style with strong ownership and excellent communication skills (written and verbal) are vital.