Join EY's GDS AI & Data team to tackle intricate business challenges using cutting-edge data and technology solutions. We specialize in extracting maximum value from data to uncover opportunities across diverse sectors including Manufacturing, Healthcare, Retail, Energy, Auto, Supply Chain, HR, and Finance.

This senior, client-facing Data Architect role involves engaging C-suite stakeholders, transforming complex business problems into robust data architectures, and leading the development of modern, cloud-native data platforms. Exceptional consultative skills, profound technical expertise, and a proven track record in architecting large-scale enterprise data ecosystems are essential. A strong understanding of at least one key sector (Healthcare, Consumer, Energy, Manufacturing, Auto, or TMT) is also required.

Lead the design and implementation of advanced cloud and data platforms across Azure, AWS, and GCP. This includes hands-on experience with Azure Data Services (Synapse, ADF, ADB, Azure SQL, Data Lake, Microsoft Fabric), Snowflake/Databricks, and programming languages like Python, PySpark, and SQL. Expertise in streaming technologies such as Kafka, Event Hubs, and Spark Streaming, as well as BI tools like Power BI and Tableau, is crucial.

Master modern data platform concepts, AI-ready data strategies, and various data modeling techniques (Dimensional, Data Vault). You'll also be responsible for metadata management, data observability, governance, and optimizing performance in distributed computing environments.

Leverage exceptional consulting abilities to advise executives on data strategy, modernization, and value creation. Strong communication, storytelling, and stakeholder management are key to leading large-scale enterprise data transformations. Familiarity with AI/ML platforms like Azure Machine Learning, Cognitive Services, and Azure OpenAI, and understanding how to architect AI-ready data is also expected.

We are seeking candidates with a minimum of 16 years of industry experience, including over 7 years focused on data architecture and analytics. A demonstrated history of successful enterprise-grade solution implementations and experience managing global stakeholders is vital. You should have a proven ability to drive significant business outcomes and possess a deep understanding of data strategy, cloud-native architectures, and analytics modernization.

Crucially, strong pre-sales experience is required, including leading and supporting deals, responding to RFPs/RFIs, creating technical documentation, and facilitating solution design workshops. Ideal candidates will also possess strong client management skills and experience in solutioning and pre-sales engagements. Familiarity with concepts such as data mesh, data fabric, and multi-cloud data strategies, alongside an interest in real-time analytics, would be advantageous.