BI Lead (Power BI/Tableau
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Role details
Tech stack
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Job description
- 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.
Requirements
We have an urgent requirement for a Lead BI professional with strong expertise in both Power BI and Tableau.
NOTE - The ideal candidate should have extensive hands-on experience with Power BI and a solid background in Tableau. In recent years, they should have been working in a Lead or Architect capacity, demonstrating both technical leadership and solution ownership.
This role requires a balance of 70% hands-on development and architecture work and 30% leadership, stakeholder management, and team guidance. We are looking for someone who can actively contribute to BI solution delivery while also leading initiatives and mentoring team members., * 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.
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