Join EY and build an exceptional career within our global, inclusive, and technology-driven environment. EY Consulting Services empowers financial institutions and capital markets participants by delivering integrated services. Our Data and Analytics team tackles complex challenges, leveraging analytical practices to enhance client decision-making and drive better business outcomes.

This role focuses on designing and operating enterprise-grade Data & AI platforms utilizing Snowflake's AI Data Cloud. You will specialize in Snowflake data engineering, creating reusable platform patterns, semantic data products, and governed AI-ready datasets. The position involves integrating enterprise services, Git-based delivery, Data SRE, and advanced governance techniques, all powered by Snowflake's cutting-edge features like Cortex AI and Snowpark.

As an AI Data Platform Engineer, you will architect and implement scalable ELT/ETL frameworks using Snowflake, Snowpark Python, and related tools. Develop diverse data ingestion pipelines for batch, event-driven, CDC, and API-based patterns. Construct curated, analytics-ready, and AI-ready data products with robust quality controls and semantic context.

You will engineer reusable platform patterns for onboarding, database standards, and operational support, alongside implementing Git connectivity, CI/CD, and release automation. Integrate Snowflake with enterprise APIs, orchestration platforms, and governance tools, ensuring production reliability and adherence to platform standards.

Furthermore, you will implement Cortex AI functionalities, including Cortex Search, Analyst, and Agents, to enable AI-powered data discovery and conversational BI. Apply agentic operations for anomaly detection, incident summarization, and automated data quality recommendations.

Key responsibilities also include implementing comprehensive governance and security measures such as RBAC/ABAC, masking policies, and data lineage. Integrate with leading governance tools and build Data SRE dashboards to monitor pipeline health, query performance, data quality, and SLA adherence.

We are seeking individuals with 5-10 years of experience in data engineering, data platform operations, analytics engineering, platform engineering, or AI platform enablement. A strong track record in implementing cloud data platforms, APIs, Git connectivity, CI/CD, and governed access patterns is essential.

Candidates should possess hands-on experience with SRE practices and production operations. Preferred qualifications include certifications in relevant cloud platforms, data engineering, DevOps, security, governance, and AI/ML engineering. An architectural awareness, strong delivery ownership, and a platform engineering mindset are highly valued.

Ideal candidates are comfortable translating platform standards into reusable frameworks, secure implementation patterns, and production-ready services. The ability to mentor engineers, collaborate effectively with cross-functional teams (architects, security, SRE), and adopt emerging AI-native and agentic engineering methods is crucial for success in this role.