Senior Data Quality Analyst at cBEYONData
Arlington, Virginia, USA -
Full Time


Start Date

Immediate

Expiry Date

29 Nov, 25

Salary

0.0

Posted On

29 Aug, 25

Experience

6 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Communication Skills

Industry

Information Technology/IT

Description

cBEYONData is seeking a highly skilled and experienced Senior Data Quality Analyst to join our team in support of a multi-year SAP S/4 HANA modernization effort for a Federal customer. The focus across the broader program includes IT transformation, leveraging subject matter experts to transform business processes, requirements development, change management and human-centered design, among other IT modernization programmatic activities. If you are interested in joining a high performing team with advancement opportunities, then look no further!
The Senior Data Quality Analyst will support the Data Management Workstream Lead in driving data quality activities and coordinating across the functional teams and with PMO/System Integrator.

Responsibilities:

  • Manage and mentor the Junior Data Quality (DQ) Analysts, fostering professional growth and excellence.
  • Lead, identify and correct data issues, standardization, and deduplication.
  • Lead data profiling, using tools to analyze data quality, completeness, and structure for all data (master and transactional).
  • Complete DQ column in Data Object inventory template.
  • Delegate tasks and ensure timely delivery of high-quality outputs.
  • Develop and enforce data quality standards, rules, and best practices to improve the accuracy and consistency of critical data assets.
  • Partner with master data governance (MDG) team members to maintain and improve the quality of master data across key domains (e.g., material, customer, vendor).
  • Monitor data integration processes to ensure master data accuracy across the program.
  • Collaborate with data stewards, business units, and other system teams to define and enforce data governance policies.
  • Lead the identification of opportunities to automate data quality monitoring and validation processes.
  • Lead initiatives to streamline data quality workflows and integrate governance principles into everyday practices.
  • Ensure compliance with data privacy and regulatory standards.
  • Identify and mitigate risks associated with poor data quality.

Requirements:

  • Active DoD Secret security clearance required
  • Bachelor’s degree in a related field
  • 6 years of related work experience
  • Strong analytical, problem-solving, and decision-making skills
  • Excellent interpersonal and communication skills, capable of working with diverse teams and influencing senior management
  • Ability to work collaboratively in a team environment and adapt to changing priorities.
  • Ability to manage multiple tasks and projects simultaneously in a dynamic environment
  • Expert skills in data management tools such as Collibra
Responsibilities
  • Manage and mentor the Junior Data Quality (DQ) Analysts, fostering professional growth and excellence.
  • Lead, identify and correct data issues, standardization, and deduplication.
  • Lead data profiling, using tools to analyze data quality, completeness, and structure for all data (master and transactional).
  • Complete DQ column in Data Object inventory template.
  • Delegate tasks and ensure timely delivery of high-quality outputs.
  • Develop and enforce data quality standards, rules, and best practices to improve the accuracy and consistency of critical data assets.
  • Partner with master data governance (MDG) team members to maintain and improve the quality of master data across key domains (e.g., material, customer, vendor).
  • Monitor data integration processes to ensure master data accuracy across the program.
  • Collaborate with data stewards, business units, and other system teams to define and enforce data governance policies.
  • Lead the identification of opportunities to automate data quality monitoring and validation processes.
  • Lead initiatives to streamline data quality workflows and integrate governance principles into everyday practices.
  • Ensure compliance with data privacy and regulatory standards.
  • Identify and mitigate risks associated with poor data quality
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