Experience required - 4+ years
Job Description : Senior Looker Full Stack Engineer
Role Overview
We are seeking a Senior Looker Full Stack Engineer who will own the entire Business Intelligence (BI) and data activation stack. This role involves designing and implementing scalable data models in a cloud data warehouse (primarily Google BigQuery ), building the authoritative semantic layer in Looker , and ensuring data is delivered reliably and securely to end-users. The ideal candidate blends deep SQL and LookML expertise with a strong software engineering and platform mindset.
Key Responsibilities
1. Looker Semantic Modeling & BI Development (The Front End)
- Design, build, and maintain the organization's core data models using LookML (Looker Modeling Language), ensuring a single, trustworthy source for all critical metrics.
- Develop high-impact dashboards, visualizations, and Explores that enable business users across all departments (e.g., Finance, Marketing, Product) to self-serve and derive actionable insights.
- Implement and manage advanced Looker features, including User Attributes, Access Filters, and Custom Visualizations , to enforce data governance and security.
- Utilize the Looker API for programmatic automation of user provisioning, content migration, and embedding analytics into external applications.
2. Data Warehouse Architecture & Optimization (The Back End)
Serve as the subject matter expert for Google BigQuery (GBQ) , advising on data structure design, table schema, and optimization strategies (e.g., partitioning, clustering, ingestion time).Write, refactor, and performance-tune highly complex SQL queries to reduce query latency and manage cloud computing costs efficiently.Collaborate with Data Engineers to implement and maintain ETL / ELT transformation pipelines using modern tools like dbt (Data Build Tool) or Google Dataform , ensuring data quality and lineage.Monitor data pipeline health and freshness, establishing and reporting on Service Level Objectives (SLOs) for data delivery.3. Platform Engineering & Governance (The Full Stack)
Implement Software Development Lifecycle (SDLC) best practices for analytics code, including Git version control for LookML and transformation logic, CI / CD pipelines, and code review processes.Define and enforce data security and governance policies across both BigQuery (IAM, R / CLS) and Looker.Manage the Looker instance platform, including upgrades, performance tuning, capacity planning, and integration with other enterprise tools.Proactively identify and resolve system bottlenecks, data discrepancies, and usage inefficiencies across the entire data-to-dashboard path.Required Skills & Qualifications
5+ years of professional experience in a Data Engineering, BI, or Analytics Engineering role.Expert-level proficiency in Looker (LookML) , with demonstrable experience modeling large-scale, complex datasets.Expert-level proficiency in Advanced SQL and extensive hands-on experience with Google BigQuery (optimization, partitioning, costing).Strong experience with a data transformation framework such as dbt or Google Dataform .Proficiency in at least one scripting language for automation and data manipulation, ideally Python .Solid understanding of cloud data warehousing principles and the Google Cloud Platform (GCP) ecosystem.Experience with version control systems, particularly Git .Excellent analytical and problem-solving skills, with the ability to communicate technical concepts to a non-technical audience.Preferred Qualifications
Looker Certified Developer and / or Google Cloud Professional Data Engineer Certification .Experience with the Looker API for content or user administration automation.Familiarity with other GCP services like Cloud Composer (Airflow) , Pub / Sub , or Vertex AI .Experience with embedded analytics solutions.