Senior Corporate Data Analyst

Responsibilities

• Develops, manages, and optimizes BI solutions, including data models, dashboards, and reports.
• Acts as owner of company wide data warehouse in regard to maintenance, availability of systems data, and coordination of data integration engineers when needed.
• Works with stakeholders, including cross departments, to gather and document requirements for BI projects, enhancements, and reporting.
• Utilizes data visualization, statistical analysis, and reporting skills to present data to stakeholders in a meaningful way.
• Uses data analysis techniques to extract information and identify patterns or trends.
• Builds reports and reconcile to system data, on both a regular cadence and ad‑hoc requests.
• Develops and maintains documentation of data sources, models, and processes.
• Provides training and support to end‑users on BI tools and reports.
• Stays current with BI industry trends and best practices.
• Applies basic development skills working with Python, SQL Queries, etc. to extract business insights around finance, business operations and more.
• Analyzes data and uses problem‑solving skills to present key insights and recommendations to various stakeholders.
• Utilizes ticketing and project management software to set, meet, and communicate deadlines and progress on assigned projects.

• Bachelor’s Degree or equivalent experience in a Computer Science, Data Analysis or business‑related field.
• Corporate Data Analyst: 1+ years’ experience working with and providing data analytics, reporting and dashboard building for company consumption.
• Senior Corporate Data Analyst: 3+ years’ experience working with and providing analytics and reporting to leadership including executive level.
• Technical experience using data manipulation tools and development languages, including Python and SQL.
• Superior communication skills.
• Strong project ownership and attention to detail skills with the ability to be a self‑starter.
• Knowledge of and experience with data pipelines and ETL processes.
• Prior experience working with data engineers and understanding of technical requirements.
• Preferred experience with Databricks, Thoughtspot, and other data lake / warehouse and analytics tools.