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Data Analyst Github Jobs in Portland, OR (NOW HIRING)

Hp

Senior Cloud Engineer

Vancouver, WA · On-site

$130K - $205K/yr

... GitHub Copilot to improve developer productivity through AI-assisted coding, code analysis ... data. Contributes to technology strategy and engineering roadmaps around software engineering ...

Esri

Sr. UX Researcher - ArcGIS Apps

Portland, OR · On-site

... GitHub issues, and release cycles * Build strong relationships and manage research projects across ... Knowledge of GIS technologies, data visualization tools, and analytical workflows * Familiarity ...

Esri

Sr. UX Researcher - ArcGIS Apps

Portland, OR · On-site

$112K - $176K/yr

... GitHub issues, and release cycles * Build strong relationships and manage research projects across ... Knowledge of GIS technologies, data visualization tools, and analytical workflows * Familiarity ...

Pwc

CTIO AI Engineering Manager

Portland, OR · On-site

$73K - $244K/yr

You will work on developing predictive models, conducting statistical analysis, and creating data ... using GitHub Actions - Implementing vector databases and orchestration tools like LangChain ...

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All JobsData Analyst Github JobsData Analyst Github Jobs in Portland, OR

Data Analyst Github information

See Portland, OR salary details

$36.1K

$87.6K

$144.2K

How much do data analyst github jobs pay per year?

As of Aug 7, 2026, the average yearly pay for data analyst github in Portland, OR is $87,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,300.00 and $102,900.00 per year, depending on experience, location, and employer.

How does a data analyst at GitHub typically collaborate with engineering and product teams?

At GitHub, Data Analysts frequently work alongside engineering and product teams to translate business questions into actionable data insights. They participate in cross-functional meetings, help define key metrics, and build dashboards or reports tailored to the needs of different stakeholders. Effective collaboration requires strong communication skills, as analysts must explain complex data findings to both technical and non-technical colleagues. This collaborative environment fosters continual learning and often provides opportunities to contribute to strategic decisions that impact the direction of products and features.

What are the key skills and qualifications needed to thrive as a data analyst at GitHub, and why are they important?

To thrive as a Data Analyst on GitHub, you need strong analytical skills, experience in statistics, and proficiency in data manipulation using languages like Python or SQL, often backed by a relevant degree. Familiarity with data visualization tools (e.g., Tableau, Power BI), Git version control, and GitHub workflows is essential, and certifications in data analysis or related fields are advantageous. Attention to detail, problem-solving, and effective communication are vital soft skills for collaborating on open-source projects and sharing insights. These competencies enable accurate data-driven decision-making, efficient project collaboration, and impactful contributions to the GitHub community.

What is a data analyst at GitHub?

Data Analysts on GitHub are professionals or contributors who use the platform to share, collaborate, and manage data analysis projects. They leverage GitHub to store datasets, share scripts and code (often in languages like Python or R), and document their analyses using tools like Jupyter Notebooks or Markdown. GitHub enables Data Analysts to version-control their work, collaborate with others through pull requests and issues, and showcase their portfolios to potential employers or collaborators.

Is GitHub good for data analysts?

GitHub is a valuable tool for data analysts as it facilitates version control, collaboration, and sharing of data projects and code. Many data analysts use GitHub to showcase their work, collaborate with teams, and manage project documentation, often integrating it with tools like Jupyter notebooks and data visualization libraries.

What is the difference between Data Analyst Github vs Data Scientist?

AspectData Analyst GithubData Scientist
Required CredentialsBachelor's in Data Analytics, Statistics, or related field; proficiency in SQL, Excel, and visualization toolsBachelor's or Master's in Data Science, Computer Science, or related; knowledge of programming languages like Python or R, machine learning
Work EnvironmentCollaborates with teams to analyze data, create dashboards, and support decision-makingBuilds models, develops algorithms, and performs advanced statistical analysis
Employer & Industry UsageUsed across industries for reporting, data visualization, and business insightsApplied in AI, predictive modeling, and complex data analysis projects

While both roles involve working with data, Data Analyst Github focuses on data visualization, reporting, and supporting business decisions, often using tools like SQL and Excel. Data Scientists perform advanced analytics, build predictive models, and require programming skills in Python or R. The roles overlap in data handling but differ in complexity and technical depth.

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Data Analyst Github jobs near you

Sr Data Analyst

BizTek People, Inc. | APA International Placement Consultants

Beaverton, OR • On-site

$90K - $114K/yr

Contractor

Re-posted 19 days ago

Job description


Job Duties:
• Develop and support data solutions in support of Supply Chain Planning reporting and analytics requirements
• Engage with product owner, technology lead, report developers, product analysts, and business partners to understand capability requirements and develop data solutions based on product backlog priorities
Requirements
Skills / Qualifications:
• 5+ years of experience with data engineering with emphasis on data analytics and reporting
• Experience developing with scripting languages such as Shell and Python
• Strong experience developing with PySpark, preferably leveraging AWS EMR managed service
• Expert experience with SQL and Relational database engineering (Oracle, SQL Server, Teradata)- expert-level SQL abilities
• Experience with agile delivery methodologies- Scrum, SAFe, Extreme Programming
• Experience working with source-code management tools such as GitHub and Jenkins
• Ability to partner with business and technology team members, to understand business requirements and translate those into value-add technology solutions
Additional preferences are:
• Experience developing solutions in Snowflake
• Experience with workload automation tools such as Airflow, Autosys.
• Knowledge of building solutions with data visualization and reporting tools (Tableau, Cognos)
• Knowledge of Supply Chain Operations / Manufacturing business processes and objectives
Skill Set
Python, SQL, Data

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