Digital Instrumentation Analyst

Role Summary: Support the setup, testing, and validation of digital tracking and market data sources that power marketing and business performance reporting. The Digital Instrumentation Analyst ensures data from pixels, tags, and external feeds is collected accurately and consistently across web and app environments.

Key Responsibilities:

Tracking & Tag Management

• Assist in implementing and testing tags using Google Tag Manager (GTM) or similar tools.

• Validate custom events, UTMs, and conversion pixels for advertising and analytics platforms (Google Ads, Meta, TikTok, etc.).

• Troubleshoot basic issues using browser developer tools and tag debugging extensions.

• Support efforts to maintain consistent tracking across domains and campaigns.

Data Quality & Validation

• Run quality assurance (QA) checks to confirm data accuracy across web and app environments.

• Help reconcile data from external market sources (e.g., box office feeds, APIs) with internal performance datasets.

• Monitor dashboards for anomalies or missing data and flag issues to senior analysts or developers.

Reporting & Documentation

• Update and maintain documentation for tag setups, data sources, and validation steps in Confluence or shared wikis.

• Contribute to Power BI or Sigma dashboards by ensuring data sources are accurate and properly connected.

• Assist in preparing recurring performance reports and help explain data discrepancies when identified.

Collaboration & Learning

• Partner with Marketing, Product, and Data Platform teams to understand campaign tracking and data requirements.

• Participate in data QA reviews and measurement framework updates.

• Learn best practices for digital analytics implementation, attribution, and privacy-compliant tracking.

Core Skills

• Tag Management: Basic experience with Google Tag Manager (GTM) or other tag management systems.

• Tracking & Conversion Pixels: Understanding of how digital advertising pixels and analytics tags (e.g., Google Ads, Meta, TikTok, Floodlight) collect data.

• Analytics QA: Ability to test and validate that events, UTMs, and data layer variables are firing correctly across web and app environments.

• Debugging Tools: Familiarity with browser developer tools (Console, Network tab) and tag validation utilities such as Tag Assistant or GA Debugger.

• Data Accuracy: Strong attention to detail and comfort identifying data inconsistencies or missing events.

• Documentation: Clear communicator who can document tag setups, QA steps, and findings in tools like Confluence or Scribe.

• Collaboration: Works well across marketing, data, and engineering teams; comfortable asking technical questions and following defined QA processes.

Originally posted on Himalayas