January 2019 – present
Working with HR Analytics team, I was tasked with cleaning up their infrastructure. Over time, the Analysts had been allowed to create tables, views and stored procedures in a production environment, where everyone had full access. This led to a host of issues, which including the QA system not being used, to production tables being accidentally deleted or the data changed.
As reports and business decisions were being made on this, people did not trust the data that was being produced.
Over the course of a year (which included time-off for parental leave), I successfully transitioned the team off of this way of working, and making their back-end system more robust, so that people could trust the data again. As part of this project, this included moving people away from an old unsupported Tableau server onto the new Tableau Server environment I had been instrumental in getting set up.
As the senior developer on the team, I am also involved in setting up some new data sets for measuring the workflow of the organization, measuring various Key Performance Indicators, like headcount and turnover. I also created a new data set that looked at individual shifts, and as this proved so useful, it is being extended to include more information. These two new data sets so far can answer over 60% of all questions the team get asked, allowing them to start focusing on other things, like R and Python for machine learning.
As part of this role, I am looking at ways to increase efficiency (eg by speeding up and optimising the disparate data loads) and innovate new datasets by joining existing datasets together and augmenting them with new information.