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Looker Lookml Jobs in Oregon (NOW HIRING)

OR

$135K - $188K/yr

BI / semantic-layer modeling experience, ideally Looker (LookML) or Omni * Strong dimensional/data-modeling fundamentals (Kimball design, star schema) * Proven ability to translate business questions ...

Looker Lookml information

What is a Looker LookML developer?

A Looker LookML Developer is a professional who specializes in creating, maintaining, and optimizing data models using LookML, the modeling language of Looker. They build scalable and efficient data structures that enable users to explore, visualize, and analyze data in the Looker platform. Their responsibilities include developing dimensions, measures, and views, ensuring data accuracy, and supporting business intelligence initiatives.

What challenges do Looker LookML developers face when collaborating with data analysts and business users?

Looker LookML developers often encounter challenges in translating business requirements into efficient data models and dashboards. Effective communication is key, as data analysts and business users may not always articulate their needs in technical terms. Additionally, balancing data model performance with flexibility for ad-hoc analysis can be complex. Working closely with stakeholders to iterate on requirements and providing clear documentation helps ensure the final product aligns with business goals while maintaining data integrity.

What skills and qualifications are needed to thrive as a Looker LookML developer?

To thrive as a Looker LookML Developer, you need a strong background in data modeling, SQL, and analytics, often supported by experience in business intelligence (BI) or data analysis roles. Proficiency with Looker, LookML, and familiarity with cloud data warehouses like BigQuery or Snowflake, as well as Looker certification, are highly valuable. Strong problem-solving skills, attention to detail, and effective communication are key soft skills for translating business requirements into actionable data insights. These skills ensure accurate data modeling, clear reporting, and the effective delivery of business intelligence solutions to stakeholders.

What is the difference between Looker Lookml vs Data Analyst?

AspectLooker LookmlData Analyst
Primary RoleDevelops and maintains data models in Looker using LookMLAnalyzes data, creates reports, and provides insights
Skills & CertificationsKnowledge of LookML, SQL, data modelingExcel, SQL, data visualization tools, analytical skills
Work EnvironmentData teams, BI departments, cloud-based platformsBusiness units, analytics teams, cross-functional teams

Looker Lookml specialists focus on building and managing data models within Looker, requiring technical skills in LookML and SQL. Data Analysts interpret data, generate reports, and support decision-making. While both roles work with data, Looker Lookml roles are more technical and model-focused, whereas Data Analysts are more business and insight-oriented.

What are popular job titles related to Looker Lookml jobs in Oregon? For Looker Lookml jobs in Oregon, the most frequently searched job titles are:

$135K - $188K/yr

Full-time

Medical, Dental, Vision

Posted 28 days ago


Job description

About Pantheon

Pantheon WebOps Platform powers the open web, running more than 300,000 sites in the cloud for customers including Google, Princeton, Salesloft and Doctors Without Borders. Every day, thousands of developers and marketers create, iterate, and scale WordPress and Drupal sites to reach billions of people globally. Pantheon's multitenant, container-based platform enables organizations to manage all of their websites from a single dashboard. Organizations including Clorox and the United Nations drive results through accelerated development and real-time publishing using Pantheon's collaborative workflows. 

The Role

Senior Analytics Engineer

The Analytics Engineering team owns how Pantheon's data becomes trusted, self-serve insight - from the data models built on our raw source tables to the semantic layer the whole company consumes. Sitting close to the business (under Finance), you'll own a domain end-to-end and act as a partner who turns business questions into the right data models.

What You Need to Succeed 

  • Own the analytics modeling lifecycle for a business domain (GTM / Lead-to-Customer or Post-Sales) - build and maintain dbt models and business marts on top of our source data in Snowflake.
  • Develop and maintain the semantic layer that powers our BI platform.
  • Partner directly with stakeholders across Finance, Sales, Marketing, CS, and RevOps to translate ambiguous business questions into the right model - prescribing or designing one when none exists.
  • Define, document, and enforce consistent metric definitions and segmentation across the org (e.g., customer lifecycle stages, production lifecycle, ARR), establishing whether each lives in dbt or the semantic layer so metrics aren't defined twice.
  • Build trustworthy self-serve data products so business partners can answer routine questions without help.
  • Collaborate with the Data Platform team where raw data is handed off - specify and request new sources, validate data, and raise quality issues upstream.

What You Bring to the Table

  • 6-8 years of overall experience in analytics, data engineering, or a related field, including at least 4 years specifically in analytics engineering.
  • Advanced SQL and hands-on experience with dbt or a comparable transformation framework (models, tests, documentation)
  • Cloud data warehouse experience, ideally Snowflake
  • BI / semantic-layer modeling experience, ideally Looker (LookML) or Omni
  • Strong dimensional/data-modeling fundamentals (Kimball design, star schema)
  • Proven ability to translate business questions into data models - strong business acumen and stakeholder communication
  • Comfortable with git and a modern analytics development workflow (branch-based PRs and code review)

Bonus Qualifications

  • SaaS finance fluency - ARR, MRR, NRR (especially valuable given we sit under Finance)
  • Depth in GTM/RevOps data (Salesforce) or post-sales/CS data (Zendesk), depending on the domain
  • Familiarity with AI- or natural-language-driven analytics
  • Exposure to orchestration (Airflow), reverse ETL, or working alongside data engineering
  • CI/CD for analytics code (e.g., dbt tests running on PRs via GitHub Actions)

What We Offer

We have all the usual perks and benefits but what we can really offer you is a fantastic work environment powered by an amazing team.

  • Industry competitive compensation and equity plan
  • Flexible time off, sick days, and 13 paid holidays
  • Comprehensive medical insurance including Health, Dental and Vision
  • Paid parental leave (plus fertility, adoption and other family planning benefits)
  • In-office workspace (San Francisco & Chicago)
  • Monthly allowance for wellness, reading and access to LinkedIn Learning for continued development
  • Events and activities both team-based and company wide that inspire, educate and cultivate

Pantheon is an equal opportunity employer and we welcome applications from all backgrounds regardless of race, color, religion, sex, national origin, ancestry, age, marital status, sexual orientation, gender identity, veteran status, disability, or any other classification protected by law. Pantheon complies with federal and local disability laws and makes reasonable accommodations for applicants and employees with disabilities. If you need a reasonable accommodation due to a disability for any part of the interview process, please contact talent@pantheon.io. Pursuant to local and federal regulations, Pantheon will consider qualified applicants with arrest and conviction records for employment.

After an offer is made and accepted, E-verify will be utilized to establish your identity and employment eligibility as required by the U.S. Department of Homeland Security.

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The US base salary range for this position in the United States is $135,000 - $188,000 USD per year. Our salary ranges are determined by role, level, and location. At Pantheon, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case.