Data Analyst

As a Data Analyst for Pure Storage, you will be responsible for performing advanced analytics including cohort analysis, scenario analysis, time series analysis, and predictive analysis. You will be creating powerful visualizations to effectively communicate the results to stakeholders. Your role will involve articulating assumptions, analyses, and interpretations of data in various modes. Your duties will also include designing data models that define the connection and storage of tables, columns, and data elements from different sources based on reporting and analytics requirements. Collaboration with BI engineers will be essential to develop efficient, highly performance, scalable reporting, and analytics solutions. You will query data from warehouses like Snowflake using SQL, validate and QA data to ensure consistent accuracy and quality, and troubleshoot data issues while conducting root cause analysis when necessary. To be successful in this role, you should possess at least 5 years of relevant experience in Data Analytics, BI Analytics, or BI Engineering, preferably with a globally recognized organization. Expertise in writing complex SQL queries for warehouses like Snowflake, Redshift, SQL Server, Oracle, or BigQuery is required. Additionally, advanced skills in designing and creating data models and dashboards in BI tools such as Tableau, Domo, Looker, etc., are essential. Intermediate proficiency in analytical tools like Excel, Google Sheets, or Power BI is also expected. Ideally, you should hold a Bachelor's or Advanced degree in Data Analytics, Data Science, Information Systems, Computer Science, Applied Math, Statistics, or a related field of study. Your willingness to collaborate with internal team members and stakeholders in different time zones is crucial for this role. This is a full-time position with a day shift schedule. The initial work mode is hybrid in Bangalore with a budget ranging from 15 to 16 LPA. Candidates with hands-on experience in live projects involving Power BI, Quick View, or Tableau are preferred.,