Project Lead with Data Analyticts with Informatica Exp - Tallahassee, United States - Comprehensive Resources Inc

Description

Role:Project Lead with Data Analyticts with Informatica Experience

Exp:10+years

Loc:Tallahassee,FL(Onsite)

Responsibilities:

• Data Discovery and Inventory: Identify, catalog, 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 cataloging 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 cataloging 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.

Minimum Qualifications:

1. Bachelor's degree in Data Science, Environmental Science, Information Science, or related studies, or equivalent work experience.

2. 3-5 years' experience in data management, metadata management, data governance, or information management.

Required KSA's:

1. 3-5 years' experience in data management, metadata management, data governance, or information management.

2. Familiarity with data dictionaries and data cataloging tools and platforms, such as Informatica. (Proficiency level – 4)

3. Understanding of data governance principles, data quality, data stewardship practices, and regulatory compliance requirements. (Proficiency level – 4)

4. Strong organizational skills and attention to detail, with the ability to accurately catalog and document complex data assets. (Proficiency level – 4)

5. Knowledge of metadata standards and frameworks, such as Dublin Core, ISO 19115, and FGDC-CSDGM. (Proficiency level – 3).

6. Ability to establish and maintain effective working relationships with others. (Proficiency level – 3)

7. Ability to work independently. (Proficiency level – 3)

8. Ability to determine work priorities and ensure proper completion of work assignments. (Proficiency level – 3)

9. Ability to effectively communicate technical standards, practices, and initiatives. (Proficiency level – 3)

Preferred KSA's:

1. Familiarity with environmental science, water quality, or related fields.

2. Experience in data management, metadata management, data governance, or information management in a scientific or environmental context.

3. Proficiency in data profiling and data analysis techniques using tools like SQL, Excel, or data profiling software.

4. Excellent analytical and problem-solving skills to identify and resolve data quality issues.

5. Basic understanding of data-related technologies and tools such as ETL, data warehouses, and data lakes.

6. Basic understanding of data visualization and reporting tools such as Qlik Sense.