Looker + GBQ Full Stack Dev

StatusNeo Inc.
San Ramon, United States of America
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

San Ramon, United States of America

Tech stack

Query Performance
API
Artificial Intelligence
Airflow
Business Analytics Applications
JIRA
Google BigQuery
Cloud Computing
Data Architecture
Information Engineering
Data Governance
Data Mart
Data Security
Data Flow Control
Performance Tuning
Data Logging
Google Cloud Platform
Sql Optimization
Snowflake
Data Strategy
Data Analytics
Google BigQuery
Looker Analytics
Data Pipelines

Job description

We are looking for an experienced Looker + GBQ Full Stack Dev to lead analytics solutioning, architecture design, and performance optimization across our enterprise-scale data ecosystem. The ideal candidate should have a strong foundation in data modeling, LookML, and Google Cloud Platform (BigQuery, Cloud Composer, Dataflow, Pub/Sub) with the ability to work directly with business stakeholders, data engineers, and visualization teams. Candidate should have good understanding of finance domain specialist who can lead the transformation agenda, and bring new insights on CFO and CEO Dashboard and understands the domain deeply. This role will anchor our BI modernization journey for Data Engineering AMS and Looker Functional teams from Functional and Domain Expertise Standpoint, ensuring scalable, secure, and performant data analytics delivery.

Key Responsibilities

  1. Architecture & Design *End-to-end Looker + GBQ Understanding, ensuring scalability and alignment with enterprise data strategy. *Define semantic layer, LookML models, and reusable data components for cross-functional BI use cases. *Create and enforce best practices for data modeling, partitioning, and optimization in BigQuery.

  2. Development & Implementation *Lead Looker dashboard and data model development for business-critical functions (Finance, Sales, Product). *Collaborate with DE & BI teams to define data pipelines feeding Looker, ensuring freshness, lineage, and consistency. *Enable parameterized and governed exploration within Looker for end-users and analysts.

  3. Governance, Security & Performance *Implement row-level and column-level security models in Looker and GBQ. *Optimize query performance and cost management within GBQ. *Drive monitoring, logging, and SLA adherence for Looker reports and data sources. *Establish automated health checks and observability dashboards across BI environments.

  4. Collaboration & Leadership *Work closely with product owners, business analysts, and DE teams to translate business KPIs into scalable data models. *Mentor and guide the Looker Functional Team and ensure alignment with global data architecture standards. *Contribute to the data governance framework, ensuring compliance with enterprise and regulatory guidelines.

  5. Continuous Improvement & Innovation *Evaluate and integrate AI/ML and advanced analytics within Looker/GBQ ecosystem where applicable. *Identify opportunities to automate operational reporting and ticket workflows (e.g., integration with Wolken or JIRA). *Drive adoption of modern Looker features (Looker Blocks, Looker API, embedded analytics).

Requirements

  • Strong proficiency in: Looker, LookML, and Looker API

  • Google BigQuery, Dataform / dbt, Cloud Composer, Pub/Sub

  • SQL optimization and cost-efficient query structuring Experience with:

  • Building scalable semantic models and data marts

  • Implementing BI and data access governance

  • Cross-functional collaboration with Data Engineering and Cloud Ops

  • Soft Skills: Excellent communication, stakeholder management, mentoring, And problem-solving ability.

Preferred Qualifications

  • Looker Certification (LookML Developer / Looker Business Analyst)
  • Google Cloud Professional Data Engineer certification
  • Experience in AMS / Managed Service environment or data product operations.
  • Exposure to Snowflake / dbt migration to GBQ is a plus.

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