Data Analyst – E-Commerce & Martech

ADT•Irving, TX

About The Position

We are looking for a data-driven, business-minded Data Analyst to join our E-Commerce and Martech pod. This role is critical to helping the team understand the health of the business, prioritize what to build next, and measure the impact of what we ship. You will work closely with Product, Engineering, and Marketing to turn data into clear insights and actionable recommendations. This is not a passive reporting role—you are expected to proactively surface opportunities, identify gaps, and influence decisions across the pod.

Requirements

3–6 years of experience in data analytics, preferably in e-commerce, marketing, or digital product environments
Proven track record of influencing product or business decisions through data
Strong experience with Google Analytics, Google Tag Manager, and Tableau
Proficiency in SQL and working with structured datasets
Understanding of event-based tracking and digital analytics implementation
Ability to move from data → insight → recommendation
Strong problem-solving skills and attention to detail
Experience analyzing funnels, A/B tests, and user behavior
Understands how digital products and marketing efforts drive business outcomes
Comfortable working in a fast-paced, cross-functional pod
Able to prioritize work based on business impact
Doesn’t wait for requests—actively surfaces insights and opportunities
Communicates clearly with both technical and non-technical stakeholders
Comfortable challenging assumptions with data

Responsibilities

Establish and maintain a clear view of E-Commerce and Marketing performance, including conversion rates, funnel performance, and drop-offs, customer acquisition and engagement metrics, and campaign and journey effectiveness.
Build dashboards and reporting that provide real-time visibility into business health.
Identify what we should work on next based on data.
Analyze user behavior to uncover friction points and opportunities.
Translate data into clear, prioritized recommendations, not just metrics.
Define success metrics and tracking plans for new features.
Analyze post-launch performance to answer: Did it move the needle? What worked and what didn’t? What should we iterate on next?
Provide clear readouts to stakeholders and leadership.
Ensure accurate tracking and instrumentation using Google Analytics and Google Tag Manager.
Partner with engineers to validate data flows and event tracking.
Identify and fix gaps in data collection.
Create and maintain dashboards using tools like Tableau.
Evaluate and propose new tools or frameworks to improve data accessibility, experimentation capabilities, and insight generation speed.
Embed data into day-to-day decision-making.
Support sprint planning and prioritization with data insights.
Educate stakeholders on how to interpret and use data effectively.