Data Analyst, Support Operations

Our client is a global leader in shipping and logistics technology, providing e-commerce businesses, online sellers, and enterprises with innovative shipping solutions. The company offers a suite of software tools that streamline order fulfillment, optimize shipping rates, and enhance delivery efficiency. Headquartered in the U.S., our client operates internationally, supporting merchants with scalable, data-driven solutions tailored to the evolving demands of global e-commerce.

The Support Operations team is responsible for delivering efficient, scalable, and high-quality customer support. Data is at the core of how we plan, execute, and measure our success. You'll work closely with Workforce Management, BI, and Support leadership to ensure that all reporting—from ticket trends to staffing insights to AI performance—is based on reliable, validated data.

Overall purpose and responsibilities of the role:

As a Data Analyst, you will leverage your expertise in SQL and passion for data validation and integrity. In this role, you'll act as the bridge between our data warehouse and operational reporting, playing a critical part in validating datasets, building trusted data connections, and ensuring the accuracy of reporting for Workforce Management and broader Support functions. You'll also contribute to scaling our AI-driven support initiatives by delivering insights on automation impact and tracking the performance of AI solutions across channels.

Duties and Responsibilities:

· Write and optimize complex SQL queries to extract, join, and transform support and workforce-related datasets

· Conduct rigorous data validation to ensure accuracy and consistency across reporting tools, dashboards, and source systems

· Develop innovative solutions to resolve data issues

· Own the data layer powering all WFM reporting—adherence, staffing, scheduling, productivity, and real-time performance

· Build dashboards and deliver insights on AI-powered support performance, including deflection rates, containment, and resolution quality

· Track and analyze customer interaction trends across support channels, including AI-assisted and automated workflows

· Present clear and precise information regarding the state of the business

· Collaborate with BI and engineering to correct logic errors, improve data structure, and ensure reporting reliability

· Partner with stakeholders to define key metrics and performance indicators related to both agent and AI-driven support

· Document data definitions, logic, and processes to maintain clarity and consistency across systems

 We leverage the following tools to power our operations:

· Google Suite & Confluence for communication and documentation

· Slack for cross-functional collaboration

· Zendesk Workforce Management for scheduling, forecasting, and real-time management

· Zendesk and Zoom Phone for support interactions

· Looker & Zendesk Explore for reporting and analysis

· Confluence for documentation

· Zapier for automation

Requirements

Must-have Skills / Qualifications:

· years of experience in a data analyst role with a strong command of SQL (window functions, CTEs, aggregation, optimization)

· years of experience with Looker or equivalent database systems

· Proven experience validating large datasets across multiple systems and resolving discrepancies

· Familiarity with support platforms (Zendesk, Assembled, Zoom Phone) and common support metrics (CSAT, SLA, AHT, deflection, etc.)

· Strong understanding of AI and automation in support, and how to measure impact (containment, escalation, satisfaction)

· Experience building clean, usable dashboards in Looker, Tableau, or similar BI tools

· Strong communication skills—you can confidently explain query logic and discrepancies to both technical and non-technical partners

· Highly detail-oriented, with a relentless commitment to data accuracy and reporting reliability

Advantageous or Nice-to-Have Skills/Experience:

· Experience supporting or scaling AI/automation efforts in support operations

· Familiarity with analyzing performance of chatbots, virtual agents, or AI deflection flows

· Experience working alongside a WFM or Support Ops team

· Knowledge of modern data stacks (BigQuery, dbt, Airflow)

· Ability to spot inefficiencies in data structure or processes and propose scalable, data-informed solutions