Vacancy expired!
Company Description
pureIntegration, a technology consulting firm with 17+ years of experience servicing fortune 100 clients, is seeking a Senior Data Engineer (Data Quality) - Remote.The ideal candidate must have outstanding communication and presentation skills, discuss technical details with engineers, and have a deep understanding of Data Quality best practices. The project resource will be primarily responsible for conducting multiple Proof of Concepts and assisting a data/ business analyst in analyzing Data Quality practices and tools and establishing a framework for the goal of obtaining organizational alignment on detecting data incidents and improving data quality. This will be a full-time role through the end of the year, with the possibility of extension into 2023.Location: Herndon, VA (Remote)Work Arrangement: 1099 Contract for a 3-4 month project, high possibility of extension into 2023Work Authorization: & USCIT only (We Do Not Sponsor H1B Visas, or work on C2C)Responsibilities:- Assisting Business Analysts in developing architectural framework templates (e.g., Enterprise data standards, business information model).
- Assisting Business Analysts in developing policy framework templates (e.g., data management, principles to enforce data standards).
- Assisting Business Analysts in defining Data Quality(DQ)and Data Dictionary (DD) use case(s) and scoring strategies for selecting the appropriate tools
- Running through a proof of concept by evaluating the use case(s) against the short-listed vendors of Data Quality and Data Dictionary tools.
- Benchmarking and selecting the optimal tools for DQ and DD.
- Establishing "golden" custom settings including install, setup, and configuration for the tools.
- Assisting Business Analysts to develop a training plan and conducting knowledge transfer.
- Bachelor's degree or master's degree in a quantitative field such as Computer Science and Information Systems, Database Management, Big Data, Data Engineering, Data Science, Applied Math, etc.
- 8 -10 Years experience in Data Engineering required.
- Experience in defining Data Quality(DQ)and Data Dictionary (DD) use case(s) and scoring strategies for selecting the appropriate tools.
- Experience in developing policy framework templates (e.g., data management, principles to enforce data standards)
- Experience in benchmarking and selecting the optimal tools for DQ and DD
- Understanding of ETL methodologies and Data Warehousing principles, approaches, technologies, and architectures including the concepts, designs, and usage of data warehouses and data marts.
Vacancy expired!