Business Intelligence Engineer

As a Senior Looker Full Stack Engineer, you will play a crucial role in owning the entire Business Intelligence (BI) and data activation stack. Your responsibilities will include designing and implementing scalable data models in a cloud data warehouse, building the authoritative semantic layer in Looker, and ensuring reliable and secure data delivery to end-users. The ideal candidate for this role should have a strong blend of deep SQL and LookML expertise along with a solid software engineering and platform mindset. Key Responsibilities: - Design, build, and maintain the organization's core data models using LookML, ensuring a single, trustworthy source for critical metrics. - Develop high-impact dashboards, visualizations, and Explores to enable self-service and derive actionable insights for business users. - Implement and manage advanced Looker features such as 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. - Serve as the subject matter expert for Google BigQuery, advising on data structure design, table schema, and optimization strategies. - Write, refactor, and performance-tune 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 or Google Dataform. - Monitor data pipeline health and freshness, establishing and reporting on Service Level Objectives (SLOs) for data delivery. - Implement SDLC best practices for analytics code, including Git version control, CI/CD pipelines, and code review processes. - Define and enforce data security and governance policies across BigQuery 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 data-to-dashboard path. Qualifications Required: - 5+ years of professional experience in Data Engineering, BI, or Analytics Engineering. - Expert-level proficiency in Looker (LookML) and Advanced SQL with extensive hands-on experience in Google BigQuery. - Strong experience with a data transformation framework like dbt or Google Dataform. - Proficiency in at least one scripting language for automation and data manipulation, preferably Python. - Solid understanding of cloud data warehousing principles and the Google Cloud Platform 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.,