Data Quality Engineer - Chantilly, United States - QinetiQ

Description

Company Overview We are a world-class team of professionals who deliver next generation technology and products in robotic and autonomous platforms, ground, soldier, and maritime systems in 50+ locations world-wide.

Much of our work contributes to innovative research in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI), machine learning (ML), and augmented reality (AR).

QinetiQ US's dedicated experts in defense, aerospace, security, and related fields all work together to explore new ways of protecting the American Warfighter, Security Forces, and Allies.

Being a part of QinetiQ US means being central to the safety and security of the world around us.

Partnering with our customers, we help save lives; reduce risks to society; and maintain the global infrastructure on which we all depend.

Why Join QinetiQ US? If you have the courage to take on a wide variety of complex challenges, then you will experience a unique working environment where innovative teams blend different perspectives, disciplines, and technologies to discover new ways of solving complex problems.

In our diverse and inclusive environment, you can be authentic, feel valued, be respected, and realize your full potential.

QinetiQ US will support you with workplace flexibility, a commitment to the health and well-being of you and your family and provide opportunities to work with a purpose.

We are committed to supporting your success in both your professional and personal lives. Position Overview We are seeking a Data Quality Engineer who will support the critical functions for mission clients. This individual will evaluate the quality of data received from data sources to assess changes/updates with existing data flows. Responsibilities
Evaluate conditioned data to ensure data is properly mapped and ready for User Acceptance Testing (UAT)
Work with technical support teams and business process owners for investigation and resolution of production quality control failures that affect operations service delivery
Create or update data models to ensure that data is stored in an organized manner
Develop processes and procedures to support the operating quality and efficiency of quality control checks in the production environment
Create and implement plans to improve data quality by identifying causes of errors or discrepancies and determining effective solutions
Work closely with all teams necessary to implement, measure, and improve quality standards for new and existing production functionality
Work with service providers to establish procedures for data collection and analysis
Consult with service providers and customers to determine how new data standards could affect operations
Document data quality issues and recommending solutions to problems
Required Qualifications
Active TS/SCI clearance with polygraph required #qinetiqclearedjob
Demonstrated experience providing data support to data engineering, and ETL teams
Experience in SQL testing experience
Ability to work closely with highly technical IT database, development, and infrastructure staff
Experience working with IT development teams, and infrastructure support organizations
Ability to effectively communicate issues in writing and orally at appropriate levels of detail for executive audiences, business stakeholders and technical teams
Experience in supporting processes for the technical and operational architecture of complex enterprise systems
Preferred Qualifications Experience with Python or PySpark Scripting is desired


Company EEO Statement Accessibility/Accommodation:

If because of a medical condition or disability you need a reasonable accommodation for any part of the employment process, please send an e-mail to [emailprotected] or call Opt.

4 and let us know the nature of your request and contact information. QinetiQ US is an Equal Opportunity/Affirmative Action employer.

All Qualified Applicants will receive equal consideration for employment without regard to race, age, color, religion, creed, sex, sexual orientation, gender identity, national origin, disability, or protected Veteran status.