About the role
A Web Analytics Developer job description covers implementing tracking code on websites, analyzing traffic data, and reporting on user behavior and conversion. The role delivers the insight marketing and web teams need to improve the site and measure campaign results. Hiring managers should assess data analysis, JavaScript, troubleshooting, and AI fluency.
A Web Analytics Developer implements tracking code on websites, pulls and analyzes traffic data, and reports on user behavior and conversion. Their findings help marketing and web teams decide how to improve the site. Alternative titles include digital analytics developer and web analytics engineer.
Typical duties include:
Tracking code. Implement and maintain web analytics tracking code throughout the website.
Traffic analysis. Extract and analyze web traffic data and patterns using web analytics tools.
Reporting. Provide detailed reports on website performance, user behaviors, and conversion rates.
What are the essential web analytics developer skills?
The essential skills are data analysis, analytical and data-driven thinking, JavaScript for tracking code, troubleshooting, and AI fluency.
Skill | Why it matters | Bryq assessment and level |
|---|---|---|
Data analysis | Turns traffic data into reliable findings | Data Analysis (advanced) |
Analytical and data-driven thinking | Supports clear recommendations from patterns in the data | Analytical Skills (advanced) |
JavaScript for tracking code implementation | Puts tracking in place across the website | Javascript (intermediate) |
Troubleshooting tracking and data issues | Keeps tracking and reported data accurate | Troubleshooting (intermediate) |
AI Fluency | Speeds up querying, anomaly detection, and report drafting | AI Fluency Assessment (functional) |
The core work is installing tracking code, extracting traffic data, and turning it into performance reports. Data analysis and analytical thinking turn raw numbers into findings. JavaScript puts the tracking in place, and troubleshooting keeps the data accurate. AI fluency speeds up querying and reporting.
Levels are a starting point. Bryq lets you set the level each role needs.
Which nice-to-have skills help a web analytics developer stand out?
SQL, dashboards and data visualization, HTML, and cross-team communication add value but are not needed on day one.
SQL. Helps extract traffic data directly.
Dashboards and data visualization. Makes findings easier to share.
HTML. Supports page markup and tag placement.
Cross-team communication. Helps explain findings to other teams.
Use these skills as tie-breakers between candidates who are equally strong on the essentials. Never screen out candidates who can learn them on the job.
Which competencies predict success as a web analytics developer?
The essential competencies are Learning Agility and Communication.
Learning Agility. Analytics tools, tracking standards, and practices keep changing.
Communication. Reports and recommendations must be clear to marketing and cross-functional teams.
Empathy adds an understanding of user behavior, and Leadership Potential adds the ability to influence decisions.
What AI skills does a web analytics developer need?
A Web Analytics Developer should use AI to speed up data querying, pattern detection, and reporting, and verify the results, which makes AI fluency a daily skill. Three use cases stand out:
AI tools now speed up much of analytics work, so the developer needs to use them daily. The output still has to be checked against the underlying data. Unchecked AI output can put wrong numbers into reports that guide marketing decisions.
Tracking scripts. Use AI to draft and debug tracking scripts and tag configurations, then test them before deployment.
Data summaries. Use AI to summarize traffic and conversion data and flag anomalies or trends for further review.
Draft reports. Use AI to turn raw performance metrics into draft reports and recommendations for marketing and web teams.
How do you assess web analytics developer candidates with Bryq?
Bryq measures all the essential skills and traits for a Web Analytics Developer in one integrated candidate profile: cognitive ability, personality traits, soft and hard skills, including AI fluency. Bryq builds an ideal profile for the role and matches candidates against it.
Profile Fit: measures cognitive ability and personality traits, matched against the ideal profile for the role.
Data Analysis: one of the skills assessments that tests how well candidates work with traffic data.
Analytical Skills: tests analytical and data-driven thinking.
Javascript: tests the skills behind tracking code implementation.
Troubleshooting: tests how candidates resolve tracking and data issues.
AI Fluency Assessment: tests how candidates apply AI to analytics tracking, analysis, and reporting.
Optional add-ons: SQL, Tableau, HTML, and Strategic Communication.
Competency profile: competency mapping covers Learning Agility and Communication, with Empathy and Leadership Potential as additions.
All Bryq assessments are validated by I/O psychologists. Profile Fit is independently bias-audited under New York City Local Law 144 (code4thought, April 2026). The AI Fluency Assessment is built on peer-reviewed and subject-matter expert research. A person makes every hiring decision.
Web Analytics Developer job description template
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Web Analytics Developer |
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About [Company name][Add a short description of your company.] About the roleAs a Web Analytics Developer, you will track web analytics, analyze website traffic patterns, and recommend ways to improve website effectiveness. Your work helps marketing and web teams decide how to improve the site and measure campaign results. Responsibilities
Qualifications
Skills and competencies we look for
Working with AI
What we offer
Equal opportunity[Add your equal opportunity statement.] |
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Author
The Bryq I/O Team
Bryq’s I/O Psychology Team is a group of industrial-organizational psychologists who design and validate the science behind our assessments. They write about what research says on hiring, skills, personality, and performance, and how HR leaders can apply it to make fairer, evidence-based decisions.
