Associate Data Engineer reports to the Manager of Data Services and is responsible for developing Data Engineering solutions within established guidelines and standards.

This role assists with building massive reservoirs for big data, to support ML and statistical models for Data Scientists & Statisticians. Associate Data Engineer assists with research and building of proof of concepts to test out theories recommended by Senior and Lead Data Engineers. Gains a thorough understanding of the requirements and ensure that work product aligns with customer requirements

• Works within the established development guidelines, standards, methodologies, and naming conventions
• Builds processes to ingest, process and store massive amount of data
• Assists with optimization the performance of bigdata ecosystems
• Wrangles data in support of data science projects
• Performs productionization of ML and statistical models for Data Scientists & Statisticians
• Develops, constructs, tests and maintains scalable data solutions for structured and unstructured data to support reporting, analytics, ML and AI
• Assists with research and building of proof of concepts to test out theories recommended by Senior and Lead Data Engineers
• Work complexity is low and help from senior team members is expected.  Staff Data Engineers work requires the application of a wide variety of established processes or methods.

Requirements

• Bachelor of Science in a related field
• 3 years of development experience
• ·Knowledge of CRISP-DM methodology relevant to Data Engineering i.e: Data preparation and Deployment
• Knowledge in foundational concepts and practices of Business Intelligence, Data Warehousing, Machine Learning and Artificial Intelligence using Microsoft technologies.
• Data profiling and dimension modeling techniques and creation of logical and physical data models.
• Experience working with job scheduling tools.
• Experience with SQL, C#, .NET, Python, Microsoft Fabric, Data Factory, Data Bricks, and Power BI
• Experience with Cloud Service Models: PaaS, IaaS, SaaS