Business Intelligence Lead

KEY RESPONSIBILITIES · Lead BI architecture and solution design conversations with clients, acting as the primary technical authority on data and analytics platforms. · Design, build, and optimize Power BI semantic models and Tableau data sources for enterprise-scale performance and maintainability. · Write and optimise complex DAX measures, M/Power Query transformations, and SQL queries to support accurate, high-performance reporting. · Diagnose and resolve data model issues — slow DAX, broken relationships, cardinality problems, and upstream data quality issues — quickly and systematically. · Architect dimensional data models (star schema, fact/dimension design) and semantic layers consumed across multiple BI tools. · Drive self-service BI capability: certify datasets, define governed metrics, and build enablement programmes so business teams can explore data independently. · Define BI deployment standards, CI/CD pipelines, and release governance to ensure reliable and secure analytics delivery. · Partner with data engineering teams to design analytics-ready data structures and resolve data issues at source. · Establish data governance frameworks covering data quality standards, metadata management, access controls, and KPI standardization across business units. · Mentor BI developers through code and model reviews, sharing DAX, SQL, and design best practices to raise overall team capability. MUST-HAVE SKILLS Power BI · Semantic model design and optimisation: star-schema modelling, reducing cardinality, managing relationships, aggregations, and composite models. · Advanced DAX: efficient, reusable measures; evaluation context; CALCULATE; iterator functions; time intelligence patterns. · M / Power Query: advanced transformations, query folding, incremental refresh, parameter-driven pipelines. · Power BI Service governance: certified datasets, deployment pipelines, workspaces, row-level security, gateways, and refresh scheduling. · Self-service BI: promoting dataset reuse and enabling business users to build their own reports without IT dependency. Tableau · Dashboard and data source design for enterprise-scale reporting. · Tableau Server / Tableau Cloud governance, published data sources, and performance optimisation. SQL & Data Architecture · Strong SQL: complex queries, CTEs, window functions, query optimisation, and reading execution plans. · Data warehouse and dimensional modelling: fact/dimension design, schema validation, and data lineage. · ETL/ELT understanding: diagnosing and resolving upstream data issues that affect BI layers. Communication & Stakeholder Engagement · Comfortable presenting architecture, data strategy, and roadmaps to client executives and technical leaders. · Skilled at requirements gathering from non-technical stakeholders and translating them into scalable BI solutions. · Experience leading architecture reviews, discovery workshops, and solution design sessions. GOOD TO HAVE · Snowflake: query optimisation, warehouse sizing, and integrating Snowflake with Power BI or Tableau via DirectQuery or native connectors. · Sigma Computing: cloud-native self-service analytics on Snowflake; governed metrics, semantic model integration, and business user enablement. · Experience connecting Sigma Computing with existing Power BI and Tableau ecosystems without creating governance gaps or data duplication. · Working knowledge of policy lifecycle, claims, underwriting, premiums, loss ratios, and combined ratio. · Ability to translate insurance business questions into structured KPIs, metrics hierarchies, and dashboard designs.