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Lead, Data Quality & Governance (Remote or Melbourne, FL)

Melbourne, Floride; Tallahassee, Floride

ID de l'offre 18195
Postuler Maintenant

L3Harris is dedicated to recruiting and developing diverse, high-performing talent who are passionate about what they do. Our employees are unified in a shared dedication to our customers’ mission and quest for professional growth. L3Harris provides an inclusive, engaging environment designed to empower employees and promote work-life success. Fundamental to our culture is an unwavering focus on values, dedication to our communities, and commitment to excellence in everything we do.

L3Harris Technologies is the Trusted Disruptor in the defense industry. With customers’ mission-critical needs always in mind, our employees deliver end-to-end technology solutions connecting the space, air, land, sea and cyber domains in the interest of national security.

Job Title: Lead, Data Quality & Governance  

Job Code: 18195

Job Location: Melbourne, FL or Remote elsewhere in the United States

Job Schedule: 9/80: Employees work 9 out of every 14 days – totaling 80 hours worked – and have every other Friday off

Job Description:

L3Harris Enterprise Data, Analytics, and Automation team is seeking a Lead Data Quality & Governance Specialist to manage the increasing complexity of the company’s data assets, ensuring data integrity, quality, and compliance with governance standards. This role is critical in supporting large enterprise-wide data initiatives, establishing a scalable data management framework that promotes the use of data as a strategic asset. The Lead Data Quality & Governance Specialist will define key data and quality objectives and develop a comprehensive data quality strategy that aligns with company goals. This individual will implement processes to regularly review, validate, and ensure the accuracy and completeness of data while addressing any errors or defects promptly.

Essential Functions:

  • Oversee the development and implementation of data quality processes and frameworks.
  • Collaborate with business owners to ensure data quality sign-offs and documentation.
  • Conduct regular data reconciliation and validation to ensure data integrity.
  • Develop, enforce, and maintain standards and best practices for data quality tools.
  • Ensure compliance with data governance policies and quality standards across the organization.
  • Create and maintain governance documentation for platform usage, procedures, and data pipelines.
  • Establish and implement naming conventions for data connections and pipelines.
  • Monitor data governance and quality updates, communicating them to relevant stakeholders.
  • Conduct regular risk assessments and manage mitigation plans related to data quality.
  • Provide quality assurance for data within the data platforms, ensuring compliance with business data transformation rules.
  • Maintain data dictionaries or a metadata repository to support effective data management.
  • Provide periodic reports on data quality and governance to leadership, outlining the current state and any risks or areas for improvement.
  • Establish training programs on tools and procedures used to maintain data quality, and train stakeholders on compliance with data standards.

Qualifications:

  •  Bachelor’s Degree and minimum 9 years of prior relevant experience. Graduate Degree and a minimum of 7 years of prior related experience. In lieu of a degree, minimum of 13 years of prior related experience.
  • 3 years of data integration experience with enterprise data warehouses such as Snowflake or Palantir Foundry.
  • 1 year experience in programming languages such as Python, R, SQL, and Git.

Preferred Additional Skills:

  • Understanding of data governance principles and Master Data Management (MDM) concepts.
  • Attention to detail with excellent analytical skills to solve problems and Strong attention to detail with excellent analytical skills for problem-solving and driving continuous improvement, using methodologies like Six Sigma or LEAN.
  • Expertise in data profiling and data cleansing techniques.
  • Experience with business intelligence (BI) and data visualization tools such as Tableau, Palantir Foundry, Power BI, Qlik, and data catalog products.
  • Working knowledge of data pipeline development or ETL tools such as Palantir Foundry, Azure Data Factory, SSIS, or Python, with experience building pipelines in PySpark or Spark SQL.
  • Understanding of enterprise-level data lifecycle management, including ETL/ELT processes, data standards, data governance, and consolidation initiatives, guided by DAMA DMBOK principles.
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