Associate Director - Business Intelligence Architect (Bengaluru)

EY - GDS Consulting - AI and DATA - BI Architect - Associate Director-BAT At EY, were all in to shape your future with confidence. Well help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world. EY GDS Associate Director BI Architect As part of our EY-GDS, we help our clients solve complex business challenges with the help of data and technology. We dive deep into data to extract the greatest value and discover opportunities in key business and functions like Manufacturing, Healthcare, Retail, Energy and Auto, Supply Chain, HR and Finance. The opportunity Looking for a senior, client-facing Enterprise BI Architect responsible for engaging C suite stakeholders, with deep expertise in designing and delivering large scale Business Intelligence solutions and a proven track record supporting pre sales activities, deal support, and solution shaping. This role requires a blend of technical leadership, enterprise architecture mindset, client engagement skills, and the ability to translate business needs into scalable, secure, and deliverable BI solutions that influence strategic deal outcomes. Should have a strong sector knowledge in at least one sectors Healthcare, Consumer, Energy, Manufacturing, Auto or TMT. Your key responsibilities Cloud and Modern BI Tools Deep pre-sales expertise across large-scale BI solutions using modern cloud platforms such as Azure, AWS, GCP, and tools like Power BI, Tableau, Qlik, Looker, etc Hands-on experience with: BI and Visualization - Power BI (preferred), Tableau, Qlik, Looker, etc. Cloud Data platform Microsoft Fabric, Azure Synapse, Snowflake, AWS Redshift, Google Big Query, ETL Tools - Azure Data Factory, Informatica, SSIS, Talend Programming Strong in SQL, DAX, MDX, Python/PySpark/R (good to have) Data Architecture Mastery Comprehensive knowledge of: Modern Data Platform and AI ready Data Dimensional modelling, semantic layer design, KPI definitions, reusable datasets, and enterprise reporting patterns. Metadata management, data observability, and governance, including workspace strategy, security model, and enterprise deployment patterns. Data integration concepts (ETL/ELT), data warehousing/lakehouse patterns, Performance tuning, optimization Leadership \u0026 Consulting Exceptional ability to bridge business and technology, advising executives on BI modernization, and value creation. Robust communication, storytelling, and stakeholder management skills. Proven experience in leading large-scale enterprise Business Intelligence solutions. AI \u0026 Advanced Analytics Exposure Exposure to AI/ML platforms such as Azure Machine Learning, Cognitive Services, and Azure OpenAI, and their integration with enterprise BI Understanding of AI ready data architectures and how advanced analytics and GenAI capabilities enhance enterprise reporting and decision-making Ability to position AI enabled BI use cases (e.g., intelligent insights, natural language querying, automated analytics) during pre sales and solutioning discussions Skills and Attributes for Success Strong understanding of cloud native data and BI architectures across Azure, AWS, or GCP, and modern analytics modernization patterns Hands-on experience with: BI and Visualization - Power BI (preferred), Tableau, Qlik, Looker, etc. Cloud Data platform Microsoft Fabric, Azure Synapse, Snowflake, AWS Redshift, Google Big Query, ETL Tools - Azure Data Factory, Informatica, SSIS, Talend Programming Strong in SQL, DAX, MDX, Python/PySpark/R (good to have) Comprehensive applied knowledge of: Data modelling (dimensional, Kimball, Hybrid) Data governance, metadata management, and data observability Performance tuning and optimization across data models, semantic layers, and BI reports/dashboards Strong stakeholder management and ability to bridge business and technology, translating complex requirements into scalable BI and analytics solutions. Exposure to AI/ML platforms: Azure Machine Learning, Cognitive Services, Azure OpenAI. To Qualify for the Role, You Must Have Minimum 16+ years of industry experience, with 7+ years in BI architecture and analytics. Proven experience in enterprise-grade solution implementations. Experience in working \u0026 managing global stakeholders. Should have driven significant business outcomes as a part of their role. Strong understanding and hands-on experience in data strategy, cloud-native architectures, and analytics modernization. Have deep Pre-sales experience leading and supporting deals Experience in responding to RFPs/RFIs, creating technical documentation, and leading solution design workshops. Ideally, Youll Also Have Pre-sales, client management skills. Experience in solutioning and pre-sales engagements. Exposure to data mesh principles and domain-oriented data product design. Familiarity with data fabric, data mesh and multi-cloud data strategies. Familiarity with real-time . .