Data Engineer : Products

CACI is looking for a Data Product Engineer within the Product Strategy & Implementation team who will help improve the existing data product refresh processes and mitigate data products. At CACI we do amazing things with data. We are experts in all things consumer and location, bringing together cutting-edge analytical techniques, creative thinking and diverse perspectives to drive growth for our clients. We build some of the most highly regarded, innovative datasets in the market and our people are the best at manipulating that data to provide insight to our clients. As part of the wider Marketing Solutions Division you will be joining a 250 strong team working in over 50 markets globally. We are a growing and dynamic group of analysts, data scientists and commercially savvy business development consultants who also provide thought leadership and creative thinking. our mission is to use data-driven insight to make a commercial difference. Perform regular data product refreshes Help improve the existing data product refresh processes Help the migration of data products From SAS to Python From on-premises to AWS Follow existing workflows to refresh a subset of our existing data products Refresh existing internal and external input data sets, often sourced from surveys Re-fit ML models on the latest data Upload deliverables (outputs and documentation) to both internal and AWS resources The existing data products comprise extensive use of SAS, csv, some use of SQL, Excel and increasing use of Python There are also extensive dependencies between the products, which means that evolution of the products must be done with careful planning There is currently significant manual involvement during the processes, which we are seeking to reduce where possible Assist in the migration of the data products from SAS to Python Most of our code base is in SAS Going forward, major redevelopments of our products will take place in Python Contribute ideas to assist the migration of on-premises product processes to AWS We are in the early stages of migrating our products and update processes to AWS; Experience with SAS, Python, SQL, version control ( ideally Git/GitLab) and running in-production data product updates It would be advantageous, but not essential, to have experience with any of the following tools: Visual Studio Code, Power BI, Linux, Airflow. An appreciation of the main concepts of Data Science/Machine Learning would be useful. We use a range of predictive analytics and machine learning methodologies, including logistic regression and cluster analysis, plus some predictive time series analysis.