Senior Data Analyst

Role overview

Responsibilities

• Support analytical work from requirements specification and data gathering through analysis and presentations.
• Build reporting and dashboards that highlight performance drivers, trends, and recommended actions.
• Combine campaign and digital analytics with back-end source data to analyze client journeys.
• Develop business recommendations with team leads and present findings to varied stakeholders.
• Contribute to scalable reporting, automated processes, and team capacity.
• Continue growing capabilities through training, peers, and other resources.

Requirements

• At least 5 years of data experience, including quantitative analysis, data handling, manipulation, and reporting.
• Complex SQL querying and integration of data from multiple databases.
• Expertise in Python and PySpark, with flexibility to use both during a transition from SAS to Python.
• Experience with AWS, including SageMaker, Glue, and Lambda.
• Experience with Adobe Analytics and visualization tools such as Tableau or QuickSight, or ability to learn visualization tools on the job.
• Strong concise oral and written communication, collaboration, expectation management, and documentation skills.

Success characteristics and tools

• The role calls for curiosity, business understanding, problem-solving, and strong technical capability.
• Structured-data skills, particularly SQL, are described as essential; strong Python/PySpark capability is needed.
• The position includes digital analysis using Adobe Analytics.