Business Intelligence Engineer

Experience required - 4+ years

Role Overview

Senior Looker Full Stack Engineer

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.