Semi Senior Data Engineer
Summary
Builds and maintains scalable data pipelines and reservoirs to support analytics, ML models, and reporting using SQL, Python, and Microsoft tech stacks.
Staff 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. Staff 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 or a related field
3 years of experience
Preferred requirements:
* 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, Linux Shell Script or Microsoft Power
* Experience with Cloud Service Models: PaaS, IaaS, SaaS