Data Analyst — Irving, TX

• Serve as the embedded analyst for the Rewards and Fuel Loyalty product teams: partner with product managers to define KPIs, set up launch measurement, and report on results.

• Build and maintain master analysis tables in Databricks (SQL/Python) that track loyalty, deals and rewards, and fuel program performance.

• Build and maintain Power BI dashboards and recurring reports (e.g., member activity, promotion performance) and keep metric definitions consistent.

• Measure the performance and incrementality of offers, promotions, and partner programs using test vs. control and cohort methods.

• Analyze app engagement event data (Mixpanel) alongside transaction data in the data lake; identify and escalate data gaps and quality issues before they affect reporting.

• Deliver ad hoc deep dives (e.g., customer segmentation, member activity, offer redemption) and present clear, concise findings to product and leadership stakeholders.

• Maintain the team’s analytics initiatives and backlog tracker, and document tables, methodologies, and metric definitions so work is reusable.

Years of Experience

• 3–5+ years of experience in data analytics, product analytics, or business intelligence, including 3+ years writing SQL against large datasets.

• Required Qualifications (Non-Negotiable)

• *Highlight or Bold your Top 3 “Must-Haves” from this section

• 3+ years of advanced SQL experience (joins, window functions, CTEs) on large-scale cloud data platforms such as Databricks/Spark SQL.

• Experience building and maintaining dashboards and reporting in Power BI (or Tableau) for business stakeholders.

• Hands-on experience analyzing customer, transaction, or digital product data (e.g., loyalty programs, promotions, app engagement) to measure KPIs and business impact.

• Working proficiency in Python (pandas or similar) for data analysis.

• Strong attention to data quality, with the ability to validate data, reconcile sources, and explain discrepancies.

• Strong written and verbal communication skills, with the ability to coordinate across product, engineering, and data teams and to present findings to non-technical audiences.

7 years experience and only W2