• Lead the development, deployment, and maintenance of Power BI Dashboards, analyzing them and providing insights to executive leadership & functional leads across the organization.• Extract data from multiple sources like Teradata SQL, Snowflake, Salesforce, SharePoint, Excel and then clean and transform it to create Power BI data models which produce consistent and streamlined business intelligence results.• Collaborate with key stakeholders across verticals to deliver relevant insights based on identified KPIs to assist in business decisions.• Identify and analyze trends in data to uncover business insights to answer business questions.• Created a Power BI app used by over 500 sales team members to self-serve their data needs on the go. Saved 24 hours on each ad-hoc request.• Translate business requirements into technical data stories for the ETL team and test the changes in the Teradata/Snowflake database.• Developed complex SQL queries to decrease the size and increase the efficiency of Power BI dataflows.• Coached and mentored team members on technical skills like SQL and Power BI through weekly working sessions.• Spearheaded the transition of ad-hoc request intake process from Smartsheets to Jira. Created Epics and stories in Jira. Responsible for timely completion of ad-hoc requests.

• Successfully managed data analysis requests for label transition project having 12,000 unique products with inventory worth 10M.• Analyzed sale trends of newly introduced products, enabling product management to move products into permanent assortment.• Contributed to saving of $1 million in product dispossession cost by analyzing inventory data and restricting purchase of soon to be obsolete SKUs.• Responsible for reporting product data for around 100k products to the government, gathered using complex SQL queries from Teradata and SQL server.• Managed the automation of 90% of repetitive weekly and monthly reports using macros, VBA and Power Automate, saving 5-man hours every week.• Successfully managed the timely completion of around 20 ad-hoc data analysis requests weekly.

• Recommend changes to production parameters after finding insights from production data in excel, generating 2% increase in production.• Achieved 80% automation for repetitive daily and weekly production reports using macros and VBA, resulting in 20% decrease in overtime hours.• Forecasted seasonal demand increase of diesel using linear regression, resulting in 20% drop in back orders compared to prior year.• Led financial analysis of gross margin projects by analyzing their economic aspects like ROI, gross margin, net profit.• Built a business case to expand the Nitrogen plant capacity using cost comparison, saving around $0.5M yearly• Automated 90% of daily and weekly production reports using VBA and macros, saving 10 % of paid overtime