- Excelled as a Senior Technical Support Engineer, taking ownership of complex customer support requests, and efficiently resolving and troubleshooting issues related to Azure Synapse Analytics- Managed blocker/production downtime scenarios, applying effective mitigations, unblocking customers, and maintaining transparent communication with stakeholders throughout the process- Partnered and coordinated with Engineering and Product Management to track, maintain and address bugs, issues and feature requests, ensuring product improvements aligned with customer needs- Supported customers using the Azure Synapse Analytics and Fabric stack which includes dedicated sql pool (MPP Big Data Warehouse), serverless sql pool, Apache spark pools, Jupyter Notebooks, and Azure data factory (workflow orchestration and data pipelines)- Guided customers through troubleshooting, cloud best practices, workload optimization, performance tuning and unblocking production down scenarios- Analyzed customer data and telemetry logs via kusto (kql), metrics and dashboards- Aided numerous Fortune 20 companies in developing and optimizing data architecture, ETL design, cost-benefit analysis, traditional and serverless warehouse design, data warehouse maintenance, and workload optimization- Served as Azure Data Factory global subject matter expert- Demonstrated leadership as a global team lead through mentoring, delivering technical presentations, sharing knowledge, providing technical coaching, training new hires, and conducting triage calls- Functioned as a reliable escalation point for fellow engineers, assisting in the resolution of highly complex and protracted issues

- Led team that architected and accelerated cloud adoption from a legacy on-premise database utilizing Data Factory, data lake, Azure Synapse Analytics, and SQL Data Warehouse (cloud relational database)- Led and Implemented enterprise wide adoption of databricks- Architected and built API pipelines with databricks, data factory and blob storage- Architected and implemented relational data warehouse on SQL Server and SSIS- Architected automated data anomaly detection and data quality monitoring model in apache spark- Developed cloud cost optimization program to incentivise analysts to bias toward frugality- Served as SME and trained internally for Power BI, Databricks, Azure Synapse Analytics, and Data Factory- Served on an internal data governance committee of senior analysts from across the company in defining a data vision, strategy, and tactics for the company- Built dashboards with Power BI, including underlying tables, ETL and reporting for over 1000 end users to drive customer revenue and retention- Worked in a cross functional team to architect, develop and deploy a marketing channel attribution model

- Built and scaled all support department reporting, data and metrics from the ground up- Owned the design, development and maintenance of KPI’s, metrics, reports anddashboards to drive key business decisions and communicate key concepts toleadership- Analyzed complex data sets utilizing SQL, Tableau and other data tools forvisualization- Converted data into actionable insight to model and predict future outcomes- Developed cloud business data warehouse architecture of WFM data to automatereporting processes- Oversaw implementation of Aspect WFM Via Cloud through the entire project life cycle- Created long term staff plan based on projected business growth resulting in increasedheadcount and a service level improvement of 30%- Analyzed historical data to create a multi-channel forecast at the interval, daily andmonthly level

- Created sales, inventory, and forecast dashboards to eliminate manual reporting and surface key metrics to business leaders- Delivered data stories to drive awareness and understanding of metrics and business performance- Built forecasting model utilizing different business rules for forecast creation and analysis resulting in 60% time saved and a 96% forecast accuracy- Created monthly sales forecast for 900 different products in six countries- Worked with C-level executives on a daily basis to make business decisions whichdrive revenue and growth- Created business plan for company across 900 products, four business units and sixcountries- Forecasted revenue within 96% accuracy- Mapped entire supply chain planning process to identify weak points

- Created client dashboards to measure and monitor contact center performance- Cleansed and wrangled contact center data for data analysis- Communicated, prepared and facilitated weekly staffing status meetings- Maintained long term staffing and capacity plans for six lines of business- Optimized staffing according to business and client service level goals and staffing needs- Automated, trained, and implemented call center overtime and VTO process- Designed and implemented forecasting process for new business- Served as Aspect WFM systems administrator for the Workforce Management team- Leveraged business data to gain client buy-in to increase headcount resulting inincreased revenue- Optimized multi-site staffing to maximize revenue

- Designed and implemented data warehouse to track forecast accuracy on a yearly, monthly, daily and interval basis- Created dashboard for daily contact center status meetings- Designed and automated call center overtime process – agents received instantapproval/denial of their requests- Analyzed historical call arrival patterns to accurately predict future staffing needs- Maintained and created staffing and budget forecasts for multiple call centergroups- Worked with management to implement shift bids/mini bids to meet service level goals- Managed efficiency goals of staff through proactively assessing the forecast toeliminate excess FTE hours worked as well as applying the appropriate overtime resulting in annual savings for the company