Embark on a fulfilling career journey at EY, where global scale and supportive culture empower you to reach your full potential. Contribute your unique perspective to enhance our organization and foster a better working world. Join us to build an exceptional experience for yourself and drive positive change for all.

EY's Consulting Services is an industry-focused unit offering integrated solutions by combining deep industry expertise with strong functional and technical capabilities. Our Data and Analytics team tackles complex challenges and seizes opportunities to deliver impactful business outcomes, securing and expanding client businesses for the future. We champion the integration of robust analytical practices into the core of client decision-making.

As a Semantic BI Engineer, you will design, build, and advise on enterprise BI and semantic analytics solutions. Your role involves transforming trusted data into actionable insights, extending beyond mere dashboard development. You will assess business needs, recommend optimal dashboarding and self-service reporting tools, architect semantic data layers, construct high-quality dashboards, and facilitate next-generation AI-assisted analytics experiences.

This multifaceted role integrates analytics engineering, semantic layer design, BI strategy, data storytelling, data modelling, AI enablement, and strong business analysis capabilities. It is ideal for professionals seeking to shape the future of analytics and drive strategic business decisions.

Architect enterprise BI and analytics roadmaps using platforms like Power BI, Microsoft Fabric, Tableau, and others. Advise stakeholders on the appropriate use of operational reporting, executive dashboards, self-service analytics, and AI-assisted insights.

Design and implement robust semantic data layers that decouple business logic from physical data structures, ensuring consistent data consumption across various tools and platforms. Define governed business metrics, KPIs, and reusable analytical entities.

Develop analytics engineering assets utilizing SQL, dbt-style transformation patterns, and Fabric semantic models. Ensure semantic models align with business glossaries, metadata, lineage, and enterprise governance standards.

Create high-impact dashboards and analytical reports to support executive decisions and operational monitoring. Translate data patterns into actionable business insights and recommendations. Leverage a variety of BI tools including Power BI, Tableau, and Snowflake Cortex Analyst.

Apply advanced data modelling techniques, including dimensional and semantic modelling, to create robust data products. Conduct in-depth data analysis using SQL and analytical thinking to identify trends, perform root-cause investigations, and support business SMEs.

Integrate AI capabilities into analytics workflows for enhanced insights, natural language querying, and automated anomaly detection. Enable AI-assisted analytics using tools like Fabric Copilot and Azure OpenAI where applicable. Design AI-ready semantic layers for conversational BI and agentic analytics.

Define and enforce governance standards for dashboards, semantic models, and certified datasets. Support integration with governance platforms like Microsoft Purview and Collibra. Develop training materials and playbooks to foster self-service analytics adoption.

A minimum of 7 years of experience in BI, analytics engineering, data analysis, semantic modelling, data modelling, or analytics architecture is required. You should possess strong hands-on experience in developing dashboards and semantic models, with a proven ability to guide businesses in selecting the most suitable BI and self-service analytics tools.

Key technical proficiencies include expertise in BI platforms such as Power BI, Microsoft Fabric, Tableau, ThoughtSpot, Qlik, Databricks AI/BI, and Snowflake Cortex Analyst. Experience with semantic and analytics engineering concepts, including semantic layers, Fabric Semantic Models, and SQL-based transformations, is essential.

Strong data modelling skills, encompassing dimensional modelling, star schema design, and metric modelling, are expected. Proficiency in data analysis techniques, including advanced SQL, trend analysis, and root-cause analysis, is crucial. Familiarity with AI and next-generation analytics tools like Fabric Copilot, Power BI Copilot, and Azure OpenAI is highly advantageous.

Experience with governance and operations tools such as Microsoft Purview, Collibra, Unity Catalog, and Immuta, along with a solid understanding of data lineage and access controls, is also required. Candidates should demonstrate an architect's mindset, with the ability to influence BI strategy and analytics consumption architecture, coupled with excellent stakeholder management and business consulting skills.