
The BI Engineer is responsible for designing and managing the Looker semantic layer, developing dashboards and reports, and enabling self‑service BI for business users. The role partners closely with Data Engineers to ensure analytics datasets are well‑modeled, performant, and governed. Strong SQL expertise is mandatory, along with hands‑on experience in Looker LookML modeling, dashboard development, backend semanticlayer and analytics best practices
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Key Accountabilities (WHAT)
Key Tasks (HOW)(RESULT)
1
Looker Semantic Modeling & Metrics Layer
· Design and maintain LookML models (views, explores, derived tables).
· Define consistent business metrics, dimensions, and calculations.
· Implement reusable measures, joins, and aggregate awareness.
· Optimize semantic models for performance and usability.
· Align semantic definitions with data engineering and business stakeholders.
· Governed LookML semantic models aligned to business domains.
· Certified explores with standardized metrics and dimensions.
· Metric definitions and business logic documentation.
· Semantic layer performance optimization artifacts.
2
Dashboard & Report Development
· Design and develop interactive Looker dashboards and reports.
· Translate business requirements into clear, actionable visualizations.
· Apply visualization best practices for usability and storytelling.
· Implement dashboard filters, drill‑downs, and user‑level access.
· Maintain and enhance existing dashboards based on feedback.
· Production‑ready Looker dashboards and reports.
· Dashboard design standards and templates.
3
Self‑Service BI Enablement
· Enable business users with the tool to explore data using certified Looker explores.
· Design user‑friendly semantic models to reduce ad‑hoc SQL dependency.
· Provide training, demos, and best‑practice guidance to users.
· Define data governance guardrails for self‑service analytics.
· Self‑service‑ready Looker explores with certified fields.
· User enablement materials (how‑to guides, training decks).
· Reduced ad‑hoc reporting backlog.
· Adoption metrics and usage insights.
4
In DB Sematic Layer and SQL Development
· Write and optimize complex SQL queries for analytics use cases.
· Validate data accuracy, aggregations, and business logic.
· Partner with Data Engineers to optimize tables, partitions, and models.
· Troubleshoot data discrepancies and performance issues.
· Optimized SQL logic supporting Looker models and dashboards.
· Query validation and reconciliation results.
5
Operations, Monitoring & Continuous Improvement
· Monitor dashboard performance, usage, and failures.
· Maintain Looker content lifecycle (dev → prod).
· Implement access controls and content organization.
· Continuously improve models and dashboards based on usage analytics.
· Stable,performant Looker environment.
· Usage and adoption reports.
Coordination with Business and Technical Vendors
. Experience - (Minimum Knowledge to Perform the Job Effectively)
# Of Years (xx)
· 5+ years of experience as a BI Engineer.
Skills Required
Technical/Managerial
Technical:
· Experience with BigQuery or other cloud data warehouses.
· Strong SQL expertise (mandatory).
· Hands‑on experience with Looker and LookML.
· Experience building enterprise dashboards and semantic layers.
· Solid understanding of data warehousing concepts and analytics modeling.
· Ability to work closely with Data Engineers and business stakeholders.
· [Optional] PowerBI and Other BI Tools
Other Requirements (If Any)
· Bachelor’s degree in Computer Science, Information Technology, Information Systems, or a related