Data Analyst-Operations & CX
New
J
JobgetherTechnology
Based in United StatesContractMiddle
Salary not disclosed
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Job Details
- Experience
- 3+ years
- Required Skills
- PythonSQLData AnalysisZendeskLookerR
Requirements
- 3+ years of experience in Data Analytics, ideally supporting Operations, Customer Experience, Quality, or high-growth technology environments.
- Advanced SQL skills with the ability to independently write complex and optimized queries, particularly in Google BigQuery.
- Proven experience creating advanced, user-friendly dashboards and data models using Looker, with LookML knowledge considered a strong advantage.
- Strong analytical mindset with experience turning data into strategic recommendations and influencing operational or product decisions.
- Experience building business cases, measuring impact, and using analytics to support prioritization of high-value initiatives.
- Excellent communication skills with the ability to explain complex data insights clearly to global, non-technical stakeholders.
- Comfortable working in remote, fast-paced environments with cross-functional teams.
- Preferred experience with Python or R for statistical analysis, automation, or predictive modeling.
- Previous experience in travel technology, telecommunications, customer support platforms, or similar industries is a plus.
- Familiarity with Zendesk, Intercom, or customer support data structures is beneficial.
Responsibilities
- Design, build, and maintain scalable dashboards and reporting solutions using Looker and BigQuery to provide reliable insights into operational performance and customer health.
- Analyze key business metrics such as customer satisfaction, NPS, contact rates, agent performance, and operational efficiency indicators to uncover trends and improvement opportunities.
- Conduct deep-dive analyses to identify root causes behind performance changes and translate findings into actionable business recommendations.
- Build data-driven business cases by quantifying potential impact, ROI, and operational improvements to support strategic decision-making.
- Develop automation solutions, scripts, and analytical tools that streamline workflows, improve efficiency, and increase team productivity.
- Partner with Data Engineering teams to maintain data quality, improve governance, and establish consistent definitions for key metrics across departments.
- Transform complex technical analysis into clear narratives and presentations that enable non-technical stakeholders to make informed decisions.
- Support Operations, Customer Experience, and Quality teams by providing insights that improve customer outcomes and business processes.
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