Typically in Computer Science, Data Science, Statistics, or a related field.
Hands on 6-10 years of relevant experience in data analysis, reporting, and visualization roles, with proficiency in the above-mentioned tools and technologies.
Experience in building best in class visualizations and working with multiple dimensions and measures.
Proficiency in writing complex SQL queries to extract and manipulate data from databases (e.g., MySQL, PostgreSQL, SQL Server).
Data Analysis and Visualization Tools: Advanced experience with tools such as Excel (including advanced functions like Index/Match, PivotTables), Tableau, Qlik Sense and/or QlikView (preferable Qlik Sense).
Programming Languages: Familiarity with scripting languages like Python and Angular for data manipulation, automation tasks and UI creation.
ETL (Extract, Transform, Load): Understanding of ETL processes and experience in tools like Talend (e.g., Informatica, SSIS) to prepare data for reporting.
Data Warehousing Concepts: Knowledge of data warehousing principles and methodologies.
Dashboard Design: Experience in design of rapid dashboard prototypes. Ability to design intuitive and insightful dashboards that effectively communicate data trends and insights.
Data Modeling: Understanding of data modeling techniques and best practices.
Version Control: Familiarity with Git or similar version control systems for managing report development.
Experience in analysis of future trends and forecasting.
Analytical Thinking: Ability to analyze complex data sets and identify trends or anomalies.
Ensuring accuracy and completeness of reports and data visualizations.
Communication: Clear communication of data insights to stakeholders, both verbally and in writing.
Problem-Solving: Ability to troubleshoot data issues and optimize report performance.
Prioritizing tasks and meeting reporting deadlines.
Understanding of business processes and requirements to tailor reports to stakeholders' needs.
Data Governance: Knowledge of data governance principles and compliance requirements.
Basic understanding to integrate predictive analytics into reports if needed.
Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) for managing and analyzing large datasets