We are looking for a skilled and hands-on Looker BI Senior Analyst to join our analytics team. You will own the design, development and governance of our Google Looker semantic layer, and help power a natural-language, conversational analytics experience that lets business teams get reliable answers directly from data. This is a senior, hands-on role that blends deep LookML and semantic-layer expertise with strong stakeholder management, as you help expand our reporting capabilities, onboard new data sources, and support data quality and validation best practices across the platform.

Key Responsibilities

Semantic Layer & LookML Development

- Design, build, and maintain LookML data models, Explores, Views, and derived tables in Google Looker
- Improve and strengthen LookML relationships, measures, dimensions, and descriptions to support a reliable semantic foundation
- Own and evolve the semantic layer to ensure consistent, reusable business logic across dashboards, reports, and natural-language queries
- Define and enforce naming conventions, governance standards, and documentation for the semantic layer
- Collaborate with data engineering to align semantic-layer design with upstream data source structures

Conversational Analytics & AI Agent Support
- Guide and support configuration of natural-language, conversational analytics agents built on top of the Looker semantic layer
- Advise on single-agent vs. multiple-agent approaches based on usability, coverage, and existing platform capabilities
- Validate agent-generated answers for accuracy and reliability against agreed, business-approved reference results
- Identify, document, and help resolve questions the implementation cannot yet answer reliably
- Support Git integration, deployment workflows, and UAT/production environment setup for the semantic layer and agent configuration

Reporting, Dashboards & Analytics Delivery
- Build and maintain Looker dashboards, Looks, and Explores that support core business reporting across the organization
- Partner with business stakeholders across multiple personas (for example, editorial, product, and marketing) to translate reporting requirements into scalable Looker deliverables
- Expand the range of personas and delivery audiences supported by the analytics platform, including new user groups, use cases, and self-service content




- Present analytical findings and dashboard walkthroughs to both technical and non-technical stakeholders

Data Quality, QA & Validation Support
- Support and help expedite QA and validation efforts for broadly used, business-critical data to improve accuracy, consistency, and trust in reporting outputs
- Prepare and execute business validation against agreed reference results; investigate and help resolve discrepancies
- Contribute to test plans, data validation checks, and reconciliation processes across Looker models and source data
- Partner with data engineering to triage and help resolve data quality issues identified during validation

Agent Training & Best Practices Enablement
- Advise on and support agent-training and validation best practices on an ongoing basis
- Create and maintain documentation, training materials, and enablement content for internal teams and business users
- Support onboarding and upskilling of team members and stakeholders on Looker and semantic-layer usage

Data Source Onboarding & Semantic-Layer Roadmap
- Help accelerate onboarding of additional data sources into the Looker semantic layer, including integrating and validating joins and metrics for newly added sources
- Support semantic-layer roadmap development and planning, including prioritization of recent models, data sources, and capabilities
- Partner with data engineering and architecture teams to assess new data sources for integration feasibility and modeling approach

Delivery, Documentation & Stakeholder Collaboration
- Maintain a shared, prioritized backlog with the client's technical team and support business validation at agreed checkpoints
- Participate in regular progress reviews and demonstrations of completed work
- Proactively escalate source-data, access, and scope dependencies early
- Produce clear documentation, UAT support, and user guidance to support release readiness and handover





Required Skills & Qualifications
- Strong, hands-on domain expertise in Google Looker, including LookML modeling, Explores, Views, derived tables, and dashboard development
- Significant hands-on experience with semantic-layer tools and implementations (Looker or comparable platforms such as dbt Semantic Layer, Cube, or AtScale)
- Proven experience designing scalable, reusable data models and governance standards within a semantic layer
- Strong SQL skills, with the ability to write and optimize complex queries across large datasets
- Strong experience and expertise with cloud data warehouse technologies, especially BigQuery
- Experience configuring or validating AI-driven / conversational (natural-language) analytics tools built on top of a BI semantic layer
- Working knowledge of Git-based version control and deployment/UAT-to-production workflows for BI or semantic-layer platforms
- Experience partnering with business stakeholders across multiple personas to gather requirements and deliver self-service analytics
- Strong communication and stakeholder management skills, with experience presenting to both technical and business audiences
- Experience developing and maintaining technical documentation and training/enablement materials
- Senior-level experience in BI/analytics engineering roles, with demonstrated ownership of end-to-end reporting solutions
- Comfortable working within a client's existing, approved tooling and platform constraints, and partnering closely with a separate data engineering team that owns upstream data preparation

Nice to Have
- Experience with QA / data validation frameworks or data engineering practices (pipeline testing, reconciliation, automated validation)
- Familiarity with agent-training or AI/ML model validation workflows
- Experience onboarding new data sources into a BI or semantic-layer platform
- Experience with additional cloud data warehouse platforms (e.g., Snowflake, Redshift)
- Experience with ETL/ELT tools and data workflow orchestrators (e.g., Airflow, dbt, Fivetran)
- Domain experience within editorial and/or marketing functions (e.g., content performance, audience engagement, and campaign reporting)
- Prior experience in a client-facing or consulting environment supporting multiple stakeholder groups

📌 Looker BI Senior Analyst (Chandigarh)
🏢 Trantor
📍 Chandigarh