Develop and design data pipelines to support end-to-end solutions.
Build systems that collect, manage, and convert raw data into usable information for multiple purposes, including, but not limited to, IT application usage, reporting, applicant processing, etc.
Develop and maintain artifacts, i.e., schemas, data dictionaries, and transforms related to ETL processes.
Integrate data pipelines with AWS cloud services to extract meaningful insights.
Manage production data within multiple datasets, ensuring fault tolerance and redundancy.
Design and develop robust and functional dataflows to support raw data and expected data.
Collaborate with the rest of the data engineering team to design and launch new features. Includes coordination and documentation of dataflows, capabilities, etc.
Requirements
Bachelor's degree.
4 - 8 years of relevant experience.
Experience executing data science methods using Python libraries for Data Cleaning/Wrangling, Exploratory Data Analysis (EDA), Statistical Analysis, and Data Visualization.
Strong proficiency in programming languages, such as Python.
Agile development experience along with related technologies (e.g., Jira).