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Google Looker Developer Jobs in California (NOW HIRING)

Viasat, Inc.

CD&A Data Engineer

Carlsbad, CA · On-site

$150K - $225K/yr

... a modern Google Cloud Platform foundation built on BigQuery, Airbyte, DBT, Prefect, and Looker ... Contribute to infrastructure-as-code using Terraform; maintain YAML configs and GitHub/Azure DevOps ...

Extractable

Python Integrations Developer

San Francisco, CA · Remote

$59.25 - $81.50/hr

Google Analytics 4, Google BigQuery, Google Tag Manager, Looker Requirements Must Have * 3+ years ... Small engineering team with direct access to product decisions * Two-week sprint cycles with ...

Extractable

Python Integrations Developer

San Francisco, CA · Remote

$59.25 - $81.50/hr

Google Analytics 4, Google BigQuery, Google Tag Manager, Looker Requirements Must Have * 3+ years ... Small engineering team with direct access to product decisions * Two-week sprint cycles with ...

AEG

Sr. Web Analytics Developer

Los Angeles, CA · On-site

... Google Tag Manager (GTM) a strong plus. • Extensive experience with JavaScript, HTML, and ... Looker, Tableau, or Power BI. • Intermediate to advanced SQL proficiency preferred. • Deep ...

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Google Looker Developer information

What is the difference between Google Looker Developer vs Data Analyst?

AspectGoogle Looker DeveloperData Analyst
Primary RoleDesigns and develops data visualizations and dashboards using LookerAnalyzes data to identify trends and generate reports
Required SkillsLooker platform expertise, SQL, data modelingData analysis, Excel, SQL, reporting tools
CertificationsLooker certifications, SQL knowledgeData analysis certifications (e.g., Microsoft, Tableau)
Work EnvironmentData teams, BI departments, cloud-based platformsBusiness units, analytics teams, reporting environments

Google Looker Developers focus on creating data visualizations and dashboards using Looker, requiring expertise in Looker and SQL. Data Analysts analyze data to generate insights and reports, often using various tools. While both roles work with data, Looker Developers specialize in visualization development, whereas Data Analysts focus on data interpretation and reporting.

How difficult is it to get hired at Google?

Getting hired as a Google Looker Developer can be competitive, requiring strong technical skills in data visualization, SQL, and familiarity with Google Cloud tools. Candidates often need relevant experience, certifications, and a solid portfolio to stand out in the application process.

How much did Google pay for Looker?

Google acquired Looker in 2019 for approximately $2.6 billion. As a Google Looker Developer, understanding the company's investment highlights the importance of data analytics and business intelligence skills in the role.

What tech jobs pay 400,000 a year?

High-level roles such as senior software engineers, data architects, and cloud solutions architects can reach or exceed $400,000 annually, especially with experience, specialized skills, and in competitive industries. Positions involving leadership, advanced technical expertise, or executive responsibilities tend to offer such compensation levels.

What is the salary of Looker developer?

The salary of a Looker developer typically ranges from $80,000 to $130,000 annually, depending on experience, location, and company size. Skilled professionals with certifications and strong SQL and data modeling skills tend to earn higher salaries.
What are popular job titles related to Google Looker Developer jobs in California? For Google Looker Developer jobs in California, the most frequently searched job titles are:
What job categories do people searching Google Looker Developer jobs in California look for? The top searched job categories for Google Looker Developer jobs in California are:
What cities in California are hiring for Google Looker Developer jobs? Cities in California with the most Google Looker Developer job openings:
Google Looker Developer jobs near you

(Director/ VP Level) Senior AI Solution Architect - Data & AI Platforms(Databricks Eco system)

Balin Technologies LLC

Santa Ana, CA • On-site

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Job Title: Senior AI Solution Architect - Data & AI Platforms(Databricks Eco system)

Location: Santa Ana, CA(4days/ Week)
Duration: 6 Months (CTH)
Job Description: Primary Skills: Big Query, Vertex AI, Cloud Storage, Dataflow, Dataproc, Pub/Sub, Looker,Data Architecture, AI/ML platforms, and Generative AI solutions,datalake house architectures, modern BI platforms, ML/MLOps, Conversational Analytics, Generative AI, and Agentic AI frameworks
Secondary Skills: Looker, Tableau, Power BI, SQL, Python, Spark, Kafka

Experience

10-15+ years overall experience (with 5+ years in AI/Data Architecture roles)

Job Summary

We are seeking a highly skilled AI Solution Architect with deep expertise in Data Architecture, AI/ML platforms, and Generative AI solutions, to design and deliver scalable, secure, and enterprise-grade data and AI solutions on Google Cloud Platform (Google Cloud Platform).

The ideal candidate will have strong hands-on experience across datalake house architectures, modern BI platforms, ML/MLOps, Conversational Analytics, Generative AI, and Agentic AI frameworks, and will work closely with business, data engineering, and AI teams to drive end-to-end AI-led transformation.

Key Responsibilities

Data & Platform Architecture

  • Design and own end-to-end data architectures including ingestion, processing, storage, governance, and consumption layers
  • Architect modern data lakehouse platforms using Google Cloud Platform services (e.g., BigQuery, Dataproc, Cloud Storage)
  • Define scalable data platforms supporting batch, streaming, and real-time analytics
  • Establish data governance, metadata management, data quality, lineage, and security frameworks

AI, ML & MLOps Architecture

  • Design ML/AI architectures supporting model training, deployment, monitoring, and lifecycle management
  • Define and implement MLOps frameworks (CI/CD for ML, feature stores, model registries, observability)
  • Collaborate with data scientists to productionize ML models at scale
  • Evaluate and recommend ML frameworks, tools, and best practices

Generative AI & Agentic AI

  • Architect and implement Generative AI solutions using LLMs (e.g., text, code, embeddings, multimodal use cases)
  • Design Conversational Analytics and AI-powered BI solutions
  • Build and evaluate Agentic AI platforms, including autonomous agents, orchestration frameworks, and tool integrations
  • Lead solution evaluations, PoCs, and vendor/tool assessments for GenAI and Agent-based systems

Business Intelligence & Analytics

  • Design modern BI and analytics platforms enabling self-service analytics and AI-driven insights
  • Integrate BI tools with data lakehouse and AI layers
  • Enable semantic layers, metrics definitions, and governed analytics

Cloud & Google Cloud Platform Leadership

  • Lead architecture and solution design on Google Cloud Platform (Google Cloud Platform)
  • Utilize Google Cloud Platform services such as BigQuery, Vertex AI, Cloud Storage, Dataflow, Dataproc, Pub/Sub, Looker, and IAM
  • Ensure architectures follow best practices for security, scalability, performance, and cost optimization

Stakeholder & Technical Leadership

  • Partner with business leaders to translate business requirements into AI-driven solutions
  • Lead technical design reviews and architecture governance
  • Mentor engineers, architects, and data scientists
  • Create architecture blueprints, reference architectures, and technical documentation

Required Skills & Qualifications

Core Technical Skills

  • Strong experience in Data Architecture & Data Platforms
  • Hands-on expertise in Data Lakehouse architectures
  • Deep understanding of end-to-end data management
  • Experience with modern BI platforms and analytics ecosystems
  • Strong background in AI/ML architecture and MLOps
  • Proven experience in Conversational Analytics and Generative AI
  • Hands-on exposure to Agentic AI platforms, frameworks, and evaluations
  • Strong expertise in Google Cloud Platform (Google Cloud Platform)

Tools & Technologies (preferred)

  • Google Cloud Platform: BigQuery, Vertex AI, Cloud Storage, Dataflow, Dataproc, Pub/Sub, Looker
  • AI/ML: TensorFlow, PyTorch, scikit-learn, LLM frameworks
  • MLOps: CI/CD, feature stores, model registries, monitoring tools
  • Data: SQL, Python, Spark, Kafka
  • BI: Looker, Tableau, Power BI (or equivalent)

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