Derive business value from enterprise data by implementing technical specifications for data storage, processing, transformation, ingestion, consumption, and automation, specifically in the healthcare industry with multiple data sources and cross-functional teams.
Requirements
- Demonstrated experience with relational and non-relational data storage models, schemas, and structures used in data lakes and warehouses for big data, business intelligence, reporting, visualization, and analytics.
- Hands-on experience with extract, transform, load (ETL) process design, data lifecycle management, metadata management, and data visualization/report generation.
- Practical experience with industry-accepted standards, best practices, and principles for implementing a well-designed enterprise data architecture.
- Data processing experience in a production environment with terabyte-sized datasets that are both structured and unstructured data.
- Required Languages: Python and SQL
- Required Libraries: PyData stack, Dask, and Prefect
- Data storage experience with Microsoft SQL Server, MongoDB, and Snowflake.
Responsibilities
- Develop, implement, and maintain enterprise data management solutions to enable organizational business intelligence, reporting, visualization, and analysis.
- Assist with the development, implementation and maintenance of an overall organizational data strategy that is in line with business processes.
- Design and build data processing flows to extract data from various sources, such as databases, API endpoints, and flat files.
- Load data into data storage systems, specifically Microsoft SQL Server, MongoDB, and Snowflake.
- Transform data using industry-standard techniques such as standardization, normalization, de-duplication, filtering, projection, and aggregation.
- Build and maintain data processing environments, including hardware and software infrastructure.
- Collaborate with data producers, consumers, and subject matter experts to ensure smooth dissemination and flow of data within the organization.
Other
- Minimum of 2+ years of experience working in data-related positions with increasing responsibility and scope of duties.
- A Bachelor’s Degree, or commensurate directly related work experience, is required with a concentration in a data-related field such as Computer Science, Informatics, Mathematics, Engineering, etc.
- Ability to work in a fast-paced and rapidly changing environment while consistently meeting strict service level agreement performance requirements.
- Ability to work independently as well as ability to effectively work in a team environment and maintain strong working relationships.
- Occasional availability for after-hours work, outside of regularly scheduled hours, and limited travel may be required.
