Database Developer in Hawley, MN, United States

Developed over 100 ETL packages, some with over 50 steps, using SSIS to extract, transfer, convert, and load multiple bank cores' data into a single data warehouse daily.

During this project, I configured ten full Azure server environment developments, tests, and productions, moving data with Azure Functions and hybrid connections. I also implemented a process using a hybrid connection manager, which enabled client data to securely flow through Azure Functions from the on-premise server into the Azure server. Additionally, I streamlined the data scrubbing process by centralizing the critical data scrubbing logic into database functions and stored procedures.

For historical comparisons, I completed an ETL process that generates monthly trending tables. I also customized data calculation processes unique for each client in how they processed their general ledger accounts. Finally, I developed a flat-table building process that took SQL views with certain prefixes and created faster-loading SQL tables from that data nightly, recreating indexes and constraints. This provided faster data loading from the data warehouse, only refreshing data nightly.

A database model for an online website. Customized their login and password credentials and portfolio table for bidders to set their customization options.

The bidding platform has range indicators for the bidding amount to be increased. The data model supports one too many bids. The table also was set up to allow any customized item to be sold with some key indicator fields setup.

I optimized the database tables using correct foreign keys, indexes, and views. I created multiple stored procedures for the website to call to manage the read, write, insert, and delete functionality.

A database warehouse designed for an oil and gas service company to collect data and store it in tables I designed based on the customers' needs and data options collected externally.

I worked to isolate certain tables into child tables for better speed and performance where things could be one too many at some point, thereby future-proofing the design.

I created summary tables for data grouping data from the data lake into easier-to-report-off table structures. I optimized other tables that previously existed by setting up an archiving process where millions of rows of data were not leveraged at all by the application but were required to keep stored for audit purposes.

I then set up an automated database process to archive those records regularly. This greatly increased the performance of the queries within the application and allowed indexes to be more effective.