Creating Data Pipelines in AWS and Power BI.Creating a data lake using AWS Glue, S3, and Athena.Designing reports in Power BI.Managing a Jira project.Gathering requirements for reporting and pipelines.Led data cleaning and configuration projects in Salesforce.

· Led a small remote team designing data dashboards and reports using Power BI, SQL, Python, and R.· Responsible for eliciting and managing requirements for dashboard and KPI development projects.· Designed and built automated Power BI dashboards, and managed dashboard projects.· Advised the Data and Change Management teams to ensure data capture and cleansing processes provided value.

· Designed and carried out an experiment demonstrating that a vendor’s deep learning model provided no value to the organization.· Designed data processes for the Direct Marketing team, reducing computing time from 10+ hours to 30 minutes.· Re-designed processes for monthly transactions by credit card and direct debit worth over $2M/month.· Participated in Blackbaud CRM data conversion as a subject matter expert.· Trained and supervised analysts converting direct marketing queries to BB CRM.· Hired and supervised a co-op student working on a predictive modelling project.

· Used SQL and Power BI to build data dashboards and automation using data from a variety of sources.· Developed statistical analyses of giving trends using R and SQL, including attrition/retention and LTV.· Participated as a subject matter expert in the RFP process to replace Raiser’s Edge databases.· Filled manager’s role during his parental leave and vacations.· Transferred from the Western Canada team to the National team.

· Designed and delivered Raiser’s Edge training for Philanthropy staff across Western Canada.· Collaborated with a team of fundraisers across the country to design data entry processes.· Documented data entry standards and created user manuals.· Elicited requirements and designed reports and dashboards to fulfill requirements.· Carried out data mining to find prospects for donations.· Conducted data cleansing.