BI Lead (Power BI / Tableau)

Fa Ewjt Saasfaprod1 Open

Hybrid Gurugram Full-time Senior Data Analysis & BI

At a glance

Senior Data Analysis & BI role at Fa Ewjt Saasfaprod1. Gurugram · full-time.

Pay not stated Data Analysis & BI salary

RoleData Analysis & BI

SenioritySenior

LocationGurugram

WorkplaceHybrid

EmploymentFull-time

PostedJun 12, 2026

Role brief

dataroles summary, based on the employer's posting.

What you'll do

Lead client conversations on BI architecture and shape solutions for their data and analytics platforms
Build and tune Power BI semantic models and Tableau sources for strong performance and ongoing maintenance
Write DAX, Power Query transformations, and SQL that produce accurate reports efficiently
Troubleshoot slow calculations, faulty relationships, model cardinality, and data quality problems
Set modelling and governance standards, enable self-service reporting, and coach BI developers through reviews

What you bring

A bachelor's degree is required
You have advanced Power BI skills, including semantic modelling, DAX, Power Query, and Service governance
You can design Tableau dashboards and data sources, and work with SQL and dimensional data models
You can explain architecture to client leaders and turn non-technical needs into scalable BI solutions

Who this fits

This senior role suits someone who can advise clients on BI architecture while staying hands-on with models, queries, and reporting. The role is based in Gurugram and follows a hybrid arrangement.

From the employer

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.

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.

Bachelor's Degree

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