Data Analyst

Role Overview

Our client is seeking a Data Analyst to support its Digital Product organization. This role combines hands-on SQL analysis, data preparation and validation, and reporting to help stakeholders understand digital performance and make informed business decisions.

The consultant will work with digital/product data and related customer and transactional information, investigate data quality issues, and build or improve reports and dashboards. The ideal candidate can take an ambiguous business question through analysis to a clear explanation of the findings and their business implications.

Success requires strong SQL fundamentals, practical dashboard ownership, and a curious, detail-oriented approach to problem-solving. This individual will work independently in a remote environment while maintaining clear communication with business and technical partners.

Key Responsibilities

• Write SQL queries using joins, aggregations, and common table expressions (CTEs) to explore large datasets and answer business questions.
• Understand data granularity and relationships between sources; identify when joins, filters, or grouping introduce duplication, missing records, or misleading results.
• Investigate inconsistencies, clean data, and validate query outputs by reconciling totals, checking record counts, and comparing results with source data and business expectations.
• Build, maintain, and improve reports and dashboards using Power BI, Tableau, or a similar tool, selecting metrics and presentation approaches that support the intended audience and business decision.
• Analyze digital/product data and connect relevant customer activity and transactional information to understand performance, identify opportunities, and support customer experience and commercial decisions.
• Translate ambiguous stakeholder questions into structured analyses, clarify business goals, test assumptions, and prioritize competing explanations.
• Document data rules, query logic, and validation checks; partner with analytics and data engineering colleagues to investigate data issues and validate fixes.
• Communicate findings, recommendations, and data limitations in plain business terms, and respond to stakeholder questions using evidence.
• Manage analytical work independently, communicate progress and blockers, and proactively identify issues or opportunities that merit further investigation.

Required Qualifications

• Practical experience in data analysis, including hands-on data investigation, preparation, validation, and reporting.
• Strong SQL proficiency, including joins and aggregations, with the ability to reason about data granularity, duplicate records, and edge cases. Ability to explain query logic and independently verify results.
• Hands-on experience building or significantly improving reports and dashboards in Power BI, Tableau, or a comparable BI tool. Ability to explain the audience, metrics, and business decisions supported by the work.
• Comfort working with digital/product data and understanding how data from different sources contributes to an analysis.
• Experience investigating data quality issues, cleaning inconsistent data, and validating findings before presenting them.
• Strong analytical judgment and business acumen, with the ability to structure ambiguous questions, explore alternative explanations, and connect findings to business impact.
• Ability to describe an analytical project from the initial business problem through the approach, findings, and resulting impact.
• Clear communication with non-technical stakeholders, including explaining results in plain language and responding constructively to questions or differing interpretations.
• Strong self-management and communication habits, with the ability to work independently and remain engaged with a remote team.

Preferred Qualifications

• Experience with Databricks or a similar cloud data platform.
• Exposure to Adobe Analytics or Adobe Experience Platform (AEP).
• Experience with web, mobile app, or clickstream behavioral data.
• Prior experience supporting a digital product or e-commerce team.
• Familiarity with data flows and transformations, and experience partnering with data engineering teams to resolve data issues.