Business Intelligence Engineer

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.