BI Lead – Power BI / Tableau

Role: BI Lead (Power BI / Tableau)

Location : Gurugram

Hire Type : FTE

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 optimise 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 standardisation 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.

Bachelor's Degree

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 optimise 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 standardisation across business units.
• Mentor BI developers through code and model reviews, sharing DAX, SQL, and design best practices to raise overall team capability.