Data Management Team Lead

2 weeks ago

Tallahassee, United States Tech Army Full time

JD- Project Leader (Data Analytics and Data Management expertise) Location : Tallahassee, Florida

(ONSITE)

Job Description: Primary Work Serve as Information Manager for the Department’s Data & Analytics (D&A) Office.

Education: Bachelor’s degree in Data Science, Environmental Science, Information Science, or related studies, or equivalent work experience

Required Tasks to be performed: • Data Discovery and Inventory: Identify, catalogue, and classify data assets, including datasets, databases, and metadata. • Catalog Metadata Management: Work with data stewards to develop and maintain standardized metadata descriptions for data assets, capturing key attributes such as data source, format, structure, quality, and usage restrictions. • Taxonomy Development: Define and implement data classification schemas, taxonomies, and ontologies to organize and categorize data assets according to IT standards, domain-specific topics, themes, and attributes. • Data Profiling and Quality Assessment: Conduct data profiling and quality assessment activities to evaluate the completeness, accuracy, and consistency of data assets, identifying data gaps, anomalies, and errors, together with the data stewards and data-source Subject Matter Experts (SMEs). • Data Governance Support: Collaborate with data governance members to establish and enforce data cataloguing policies, standards, and procedures that promote consistency, reliability, and compliance with regulatory requirements. • Stakeholder Engagement: Work closely with data owners, stewards, consumers, and stakeholders across the department to understand their data needs, requirements, and priorities, and ensure that cataloged data assets meet their expectations. • Training and Documentation: Provide training and documentation support to data stewards on data cataloguing best practices, tools, and processes, enabling them to effectively discover, access, and utilize all data resources. • Leadership and Mentorship: Provide leadership, guidance, and mentorship to junior staff members and colleagues, fostering a culture of continuous learning, innovation, and excellence in D&A practices. • Implement and monitor data governance processes, including data access controls, data retention policies, and data life cycle management. • Coordinate with D&A team, data governance members, and department staff working with D&A to improve the quality, integrity, and governance of data assets within the department.

Required Knowledge Skills & Abilities • 3-5 years’ experience in data management, metadata management, data governance, or information management. • Familiarity with data dictionaries and data cataloging tools and platforms, such as Informatica. (Proficiency level – 4) • Understanding of data governance principles, data quality, data stewardship practices, and regulatory compliance requirements. (Proficiency level – 4) • Strong organizational skills and attention to detail, with the ability to accurately catalog and document complex data assets. (Proficiency level – 4) • Knowledge of metadata standards and frameworks, such as Dublin Core, ISO 19115, and FGDCCSDGM. (Proficiency level – 3) • Ability to establish and maintain effective working relationships with others. (Proficiency level – 3) • Ability to work independently. (Proficiency level – 3) • Ability to determine work priorities and ensure proper completion of work assignments. (Proficiency level – 3) • Ability to effectively communicate technical standards, practices, and initiatives. (Proficiency level – 3)

Preffered knowledge Skills & Abilities • Familiarity with environmental science, water quality, or related fields. • Experience in data management, metadata management, data governance, or information management in a scientific or environmental context. • Proficiency in data profiling and data analysis techniques using tools like SQL, Excel, or data profiling software. • Excellent analytical and problem-solving skills to identify and resolve data quality issues. • Basic understanding of data-related technologies and tools such as ETL, data warehouses, and data lakes. • Basic understanding of data visualization and reporting tools such as Qlik Sense

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