Data Analyst
Overview
The Data Analyst is a mid-to-senior level role that supports and advances the analytics agenda by collecting, analyzing, and interpreting data to improve the customer experience and business performance. This role works closely with cross-functional teams to deliver insights, maintain data integrity, and contribute to data-driven decision-making across the organization.
Essential Duties and Responsibilities
- Collect, clean, and validate data from multiple sources to ensure accuracy, consistency, and reliability.
- Develop and optimize SQL queries, reconciliation checks, and data models to support reporting and analysis needs.
- Build and maintain dashboards and reports in Tableau (or similar BI tools) that provide actionable insights to Sales, Operations, and Product teams.
- Partner with stakeholders across business units to investigate key questions and deliver clear, data-backed recommendations.
- Support customer experience analytics initiatives, including website usage, A/B testing, and integration of online/offline customer journey data.
- Apply advanced statistical methods to analyze large datasets, identify trends, and uncover business opportunities.
- Collaborate with the data engineering team on preprocessing and source alignment to improve data quality and automation.
- Document analysis processes, update internal knowledge bases, and contribute to improving analytics workflows.
- Stay current on emerging tools and technologies (e.g., Databricks, AWS) and bring forward recommendations for adoption.
Qualifications
- Master’s degree in Data Analytics, Computer Science, Information Systems, Statistics, Business Analytics, or related field.
- 3–5 years of experience in data analysis, reporting, or business intelligence within a fast-paced or enterprise environment.
- Strong SQL skills with experience writing, optimizing, and troubleshooting queries.
- Proficiency in Excel and demonstrated experience with Tableau, Power BI, or similar BI/reporting tools.
- Solid understanding of statistical methods, data modeling, and applied analytics.
- Ability to interpret complex data, translate findings into actionable insights, and clearly communicate results to technical and non-technical stakeholders.
- Experience working with cloud-based data platforms (AWS, Databricks, or similar) preferred.
- Strong organizational and problem-solving skills, with the ability to work both independently and collaboratively.
