Project Lead with Data Analyticts with Informatica Exp

3 weeks ago


Tallahassee, United States Comprehensive Resources Full time

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. Bachelors 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 KSAs:

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 KSAs:

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.



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