Data Analyst

About the role

You will own the analytics function for Tapcheck's Customer Support organization. Your job is to make sure Support leadership always has a clear, credible picture of how the team is performing and what the data says they should do about it. That means maintaining the standards for what gets measured, keeping the dashboards and frameworks that surface those metrics accurate, and producing the analyses that drive real decisions on strategy, investment, and priorities. The right candidate is comfortable working with ambiguity, can scope their own problems, and knows the difference between producing a report and driving a decision. This role offers both a remote and hybrid option. Employees located within 30 miles of Plano TX, are required to be in-office Tuesday through Thursday each week. If remote, Ideally, candidates will sit in the following states: AL, AZ, CA, CO, DC, DE, FL, GA, ID, IL, LA, MI, MA, MO, NC, NH, NJ, NV, NY, PA, OR, OH, RI, SC, TX, UT, VA, WA, WI.

Responsibilities

• Maintain the KPI standards for Customer Support: document how each metric is calculated and interpreted, keep definitions current across data platforms, and flag to leadership when targets may need adjustment.
• Build and maintain dashboards in Omni Analytics (our BI platform) that serve analyst, manager, and leadership audiences; maintain the semantic layer and metric definitions so every team measures the same things the same way.
• Produce formal analyses and recommendations on volume trends, resolution efficiency, CSAT, contact rate, and cost performance; frame findings in terms of business impact, not just numbers.
• Identify anomalies and performance gaps in Support data; bring a recommended course of action to leadership rather than a flag, and track the response through to resolution.
• Consult on SQL, Snowflake, and BI standards used for Support reporting; ensure Support modeling approach, query patterns, and tooling match organizational standards.
• Lead metric alignment conversations with Data, Product, and Engineering; represent Support's analytical interests and keep shared definitions from drifting.
• Triage and scope ad hoc analysis requests from across the organization; exercise judgment on urgency, feasibility, and which questions are worth answering.
• Where your work starts and stops:
• You own the business analytics layer: maintaining KPI standards, keeping dashboards accurate, and producing performance trend analysis. You hand off data pipeline engineering, schema changes, and infrastructure work to Data Engineering.
• You identify where automation or AI tooling could reduce Support volume and quantify the potential impact. You hand off the design, build, and deployment of those tools to the Enablement team.
• You surface VOC and customer experience signals that live in Support's data. You hand off VOC program management and external reputation response to the Reputation Manager function.
• You produce the analysis behind staffing and investment recommendations. You do not make headcount decisions or approve spend; those decisions belong to Support leadership.
• You do not own QA testing, regression validation, or system performance auditing. Those responsibilities sit with Engineering and QA.
• Who you'll work with:
• Support Operations and Support leadership: your primary stakeholders for analysis requests, metric sign-off, and performance reviews.
• Data Engineering: shared pipeline standards, Snowflake modeling, and Omni semantic layer alignment.
• Product: translating Support trends into product signals and prioritization input.
• Enablement: automation and AI decisions that reduce support contact volume, where your quantification informs their build decisions.

Requirements

• 2 to 4 years in a data analyst or business intelligence role where you owned metrics end-to-end: definition, calculation, documentation, and storytelling.
• SQL proficiency including CTEs, window functions, and query optimization; you can get to an answer without waiting on someone else to pull data for you.
• Hands-on experience building and managing dashboards in a modern BI tool (Looker, Tableau, Power BI, or similar).
• Demonstrated ability to communicate complex findings to non-technical audiences; leadership should leave your presentations knowing what to do, not just what happened.
• Comfortable scoping your own work: you can take an ambiguous business question, decide on methodology, and drive a recommendation without close direction.
• Preferred
• Experience in fintech, SaaS, or customer support operations environments.
• Familiarity with Snowflake or similar cloud data warehouses.
• Exposure to support platforms such as Zendesk and their underlying data structures.
• Experience with dbt or similar data transformation frameworks.
• Who this role is not for:
• Someone who needs a fully built metric framework before they can start measuring anything.
• Someone who wants to own automation, AI, or chatbot development; that wor

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