EY - GDS Consulting - AI And DATA -AI Data Platform Engineer - Snowflake- Senior
Ernst and Young30 days ago
Bengaluru, IndiaSenior
Responsibilities
- Design and implement Snowflake ELT/ETL frameworks using SQL, Snowpark Python, Dynamic Tables, Streams, Tasks, and Snowpipe.
- Develop batch, event-driven, CDC, streaming, API-based, and third-party service ingestion pipelines.
- Build curated, analytics-ready, and AI-ready data products with ownership, quality controls, semantic context, and defined consumption patterns.
- Optimize Snowflake workloads, virtual warehouses, clustering, query performance, storage design, and cost efficiency.
- Develop reusable platform patterns for onboarding, database and schema standards, pipeline templates, logging, monitoring, cost controls, and operational support.
- Implement Git connectivity, branching, pull requests, code reviews, CI/CD, infrastructure as code, release automation, and environment promotion.
- Integrate Snowflake with enterprise APIs, source systems, orchestration platforms, governance tools, security services, and downstream analytics consumers.
- Implement Cortex AI Functions, Cortex Search, Cortex Analyst, Cortex Agents, vector search, semantic retrieval, RAG, and conversational BI patterns.
- Apply agentic operations for anomaly detection, query and failure diagnosis, data quality recommendations, documentation generation, and incident summarization.
- Implement RBAC/ABAC, masking policies, row- and column-level security, tags, classification, lineage, audit logging, secrets management, and policy-as-code.
- Build Data SRE dashboards covering pipeline health, warehouse usage, query performance, data quality, access activity, incidents, costs, and SLA/SLO adherence.
- Support technical design reviews, deployment governance, production reliability, mentoring, and collaboration with architecture, security, and SRE teams.
Requirements
- 5–10 years of experience in data engineering, data platform operations, analytics engineering, platform engineering, or AI platform enablement.
- Strong hands-on experience with cloud data platforms, APIs, Git connectivity, CI/CD, governed access patterns, SRE practices, and production operations.
- Hands-on experience with Snowflake AI Data Cloud, Snowpark, Dynamic Tables, Streams and Tasks, Snowpipe, Data Sharing, Native Apps, and semantic data products.
- Experience with Cortex AI Functions, Cortex Search, Cortex Analyst, Cortex Agents, vector search, RAG, GraphRAG, agentic AI, and semantic retrieval.
- Experience with SQL, Python, Snowpark Python, APIs, Git, CI/CD, dbt, unit testing, integration testing, and data pipeline testing.
- Experience with AWS, Azure, or GCP and tools such as Terraform/OpenTofu, Kubernetes, Docker, GitHub Actions, Azure DevOps, Jenkins, and enterprise orchestration tools.
- Experience with governance and reliability practices including RBAC/ABAC, Immuta, Microsoft Purview, masking, row/column security, tags, classification, lineage, audit logging, data quality, Data SRE, and FinOps.
- Preferred certifications related to cloud or platform technologies, data engineering, DevOps, security, governance, and AI/ML engineering.
- Ability to translate platform standards into reusable frameworks, secure implementation patterns, operational controls, and production-ready services.
- Ability to mentor engineers, collaborate with architects, security and SRE teams, and adopt AI-native and agentic engineering methods.
Benefits
- Support, coaching, and feedback from colleagues.
- Opportunities to develop new skills and progress your career.
- Freedom and flexibility to handle the role in a way that is right for you.
- Individual progression planning, education, coaching, practical experience, challenging assignments, and an interdisciplinary knowledge-sharing environment.
Tech Stack
Categories
Data Engineering
About Ernst and Young
Ernst & Young (EY) provides audit/assurance, tax, consulting, strategy and transactions services to enterprises, financial institutions, and public‑sector clients. Structured as a global network of partner‑owned member firms, it sells professional services on a fee basis, including a dedicated Financial Services Organization for banking, insurance, and capital markets. Headquartered in London, EY was formed in 1989 from the merger of Ernst & Whinney and Arthur Young, and operates in 150+ countries.