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EY - GDS Consulting - AI And DATA - Semantic BI - Senior

Location:  Bengaluru
Other locations:  Primary Location Only
Salary: Competitive
Date:  Aug 20, 2026

Job description

Requisition ID:  1735405

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. 

 

 

 

 

EY-Consulting - Data and Analytics - Semantic BI Engineer – Senior  

 

EY's Consulting Services is a unique, industry-focused business unit that provides a broad range of integrated services that leverage deep industry experience with strong functional and technical capabilities and product knowledge. EY's financial services practice provides integrated Consulting services to financial institutions and other capital markets participants, including commercial banks, retail banks, investment banks, broker-dealers & asset management firms, and insurance firms from leading Fortune 500 Companies. Within EY's Consulting Practice, Data and Analytics team solves big, complex issues and capitalise on opportunities to deliver better working outcomes that help expand and safeguard the businesses, now and in the future. This way we help create a compelling business case for embedding the right analytical practice at the heart of client's decision-making.

 

 

Role : Semantic BI Engineer    

 

Experience Guide : 3-7 Years    

 

Primary Skill Area : Semantic Analytics, Self-Service BI, Dashboards, AI-Enabled Insights & Decision Intelligence

 

 

The opportunity

 

Design, build and advise on enterprise BI and semantic analytics solutions that convert trusted data into actionable business insights. This role is not limited to dashboard development; the candidate must be able to assess business needs, propose the right dashboarding or self-service reporting tools, design semantic data layers, build high-quality dashboards, and enable next-generation AI-assisted analytics experiences. The role combines analytics engineering, semantic layer design, dashboard architecture, BI strategy, data storytelling, data modelling, AI enablement and strong business analysis capability.

 

 

Your key responsibilities

 

  • BI Strategy, Tool Evaluation & Solution Advisory
  • Assess business reporting, analytics and self-service consumption needs across user personas, maturity levels, governance requirements and operating constraints.
  • Evaluate and recommend the right BI, dashboarding and self-service reporting tools based on scalability, semantic layer fit, governance, cost, user adoption, integration capability and AI-readiness.
  • Shape enterprise BI and analytics roadmaps across Power BI, Microsoft Fabric, Tableau, ThoughtSpot, Qlik, Databricks AI/BI, Snowflake Cortex Analyst and other modern analytics platforms.
  • Advise stakeholders on when to use operational reporting, executive dashboards, self-service analytics, semantic search, conversational BI, embedded analytics or AI-assisted insight discovery.
  • Semantic Layer & Analytics Engineering
  • Design semantic data layers that separate business logic from physical data structures and allow consistent consumption across dashboards, reporting tools, AI assistants and self-service analytics platforms.
  • Define governed business metrics, KPIs, measures, dimensions, hierarchies, calculations, data definitions and reusable analytical entities.
  • Develop analytics engineering assets using SQL, dbt-style transformation patterns, Fabric semantic models, Power BI datasets, lakehouse/warehouse tables and curated analytical data products.
  • Align semantic models with business glossaries, metadata, lineage, data quality rules, access controls and enterprise governance standards.
  • Dashboard Development, Architecture & Data Storytelling
  • Design and develop high-quality dashboards, scorecards and analytical reports that support executive decisions, operational monitoring, root-cause analysis and business performance tracking.
  • Apply dashboard design principles including KPI hierarchy, drill-through, guided navigation, narrative flow, visual consistency, usability, accessibility and performance optimisation.
  • Build dashboards using tools such as Power BI, Fabric, Tableau, ThoughtSpot, Qlik, Databricks AI/BI, Snowflake Cortex Analyst or equivalent enterprise BI platforms.
  • Move beyond visualisation by translating patterns, trends and exceptions into actionable business insights, recommendations and decision support.
  • Data Modelling, Data Analysis & Insight Generation
  • Apply strong data modelling skills including dimensional modelling, star schema design, semantic modelling, analytical data product modelling, metric modelling and data mart design.
  • Perform deep data analysis using SQL, analytical thinking, data profiling, reconciliation, segmentation, trend analysis, variance analysis and root-cause investigation.
  • Partner with business SMEs, data engineers, data architects and product owners to convert business questions into robust data models, analytical logic and reusable reporting assets.
  • Ensure insights are grounded in trusted data, explainable logic, meaningful context and clear business interpretation.
  • AI-Enabled Analytics & Next-Generation BI
  • Understand where and how AI can improve analytics workflows, including natural language querying, automated insight generation, anomaly detection, narrative summaries, semantic search and guided analysis.
  • Enable AI-assisted analytics using capabilities such as Fabric Copilot, Power BI Copilot, Databricks Genie, Databricks AI/BI, Snowflake Cortex Analyst, ThoughtSpot Spotter, Azure AI Foundry and Azure OpenAI where relevant.
  • Design AI-ready semantic layers that provide business context, trusted metrics, governed definitions and explainability for conversational BI and agentic analytics use cases.
  • Identify appropriate use cases for AI in BI while recognising where traditional dashboards, governed reports or human-led analysis remain more suitable.
  • Governance, Adoption & Analytics Operating Model
  • Define governance standards for dashboards, semantic models, KPIs, certified datasets, access controls, refresh schedules, lifecycle management and reporting asset ownership.
  • Support integration with governance and catalogue platforms such as Microsoft Purview, Collibra, Unity Catalog, Snowflake Horizon, Immuta or equivalent enterprise tools.
  • Create templates, design standards, dashboard review checklists, documentation patterns and adoption playbooks for consistent analytics delivery.
  • Enable business users through self-service analytics training, guardrails, metric definitions and trusted data consumption practices.

 

 

Skills and attributes for success

 

  • BI and dashboarding - Power BI, Microsoft Fabric, Tableau, ThoughtSpot, Qlik, Databricks AI/BI, Snowflake Cortex Analyst, executive dashboards, self-service reporting, embedded analytics.
  • Semantic and analytics engineering - Semantic layers, Fabric Semantic Models, Power BI datasets, metrics layer, governed KPIs, SQL, dbt-style modelling, analytical data products, business glossary alignment.
  • Data modelling - Dimensional modelling, star schema design, snowflake schema design, semantic modelling, metric modelling, data mart design, canonical/domain model awareness, data dictionary creation.
  • Data analysis and insight generation - Advanced SQL, data profiling, trend analysis, root-cause analysis, variance analysis, segmentation, data storytelling, business analysis, actionable insight generation.
  • AI and next-generation analytics - Fabric Copilot, Power BI Copilot, Databricks Genie, Snowflake Cortex Analyst, ThoughtSpot Spotter, Azure OpenAI, conversational BI, semantic search, AI-assisted insights, agentic analytics.
  • Governance and operations - Microsoft Purview, Collibra, Unity Catalog, Immuta, certified datasets, data lineage, access controls, dashboard governance, BI adoption, performance optimisation.

 

 

To qualify for the role, you must have

 

  • Relevant experience guide: 3-7 years
  • 3+ years of experience in BI, analytics engineering, data analysis, semantic modelling, data modelling or analytics architecture.
  • Strong hands-on experience developing dashboards and semantic models, with the ability to advise on the right BI/self-service analytics tools for business needs.
  • Preferred certifications: Power BI Data Analyst, Microsoft Fabric Analytics Engineer, Tableau, Snowflake/Databricks analytics credentials, AI/GenAI foundations or cloud data certifications.

 

 

Ideally, you'll also have

 

  • Architect by mindset, not only dashboard developer by nature; able to influence BI strategy and analytics consumption architecture.
  • Excellent data analytics, stakeholder management, business consulting and data storytelling skills.
  • Understands where AI should and should not be used in analytics workflows, and can guide business users towards trusted, governed and actionable insights.
  • Comfortable operating across business, analytics, data engineering, semantic architecture, AI and enterprise governance teams.
  • This role is not a traditional BI Developer. It is a Semantic BI Engineer and analytics architect who defines how trusted data is modelled, consumed and converted into actionable insight through governed dashboards, self-service analytics and AI-enabled decision intelligence.

 

 

What we look for

 

  • Architect by mindset, not only dashboard developer by nature; able to influence BI strategy and analytics consumption architecture.
  • Excellent data analytics, stakeholder management, business consulting and data storytelling skills.
  • Understands where AI should and should not be used in analytics workflows, and can guide business users towards trusted, governed and actionable insights.
  • Comfortable operating across business, analytics, data engineering, semantic architecture, AI and enterprise governance teams.

 

 

What working at EY offers

 

At EY, we're dedicated to helping our clients, from start-ups to Fortune 500 companies, and the work we do with them is as varied as they are.

You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasises high quality and knowledge exchange. Plus, we offer:

 

  • Support, coaching and feedback from some of the most engaging colleagues around
  • Opportunities to develop new skills and progress your career
  • The freedom and flexibility to handle your role in a way that's right for you

 

 

EY | Building a better working world 


 
EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.  


 
Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate.  


 
Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today.  

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