Data Engineer Data Management ETL
Global consulting company
Green Card holders or us citizen only
**DO not apply unless you are a Green card holder or a US citizen**
Loveland, co location
Bachelor's or Master's Degree in technical or business discipline or related experience; Master's Degree preferred.
5+ years? experience with advanced data management systems (e.g. Teradata, Hadoop etc.)
5+ years? experience in developing applications in high volume data staging/ ETL environments and is proficient in advanced SQL skills (Postgres/ SQL)
Clear understanding of different data domains in operations, customer etc., and has experience in master data management
Strong analytical and problem-solving skills paired with the ability to develop creative and efficient solutions; tolerance in dealing with bad quality data
Knowledge of developing and maintaining formal documentation that describes data and data structures including data modeling
Team oriented, goals oriented, and flexible with proven track record in collaborating with multiple stakeholders
Experience in agile methodology
Nice to have technical skills: Jira, AWS Glue, Redshift
Data Engineer to build and maintain an infrastructure for delivering customer insights from structured and unstructured data sources.
The Data Engineer will implement analytical solutions with a focus on collecting, managing, modeling, analyzing, and visualizing data and develop batch & real-time processes to move data
Ability to work with senior IT and Business leaders providing technical guidance related to data architecture, data models and meta data management
Works closely with database teams on topics related to data requirements, cleanliness, accuracy etc.
Interacts with the Business divisions to understand all data requirements to develop business insights and translates them into data structures and data model requirements to IT
Codes, tests, and documents new or modified data systems to create robust and scalable applications for data analytics
Develops standards and processes for integration projects and initiatives
Collects, parses, manages, analyzes and visualizes large sets of data using multiple platforms
Ensures that data pipelines are scalable, repeatable, and secure, and can serve multiple users within the company