Data Architecture and Governance Lead
Our client, a major international utilities company, is looking to hire a Data Architecture and Governance Lead. This role is based out of Paramus, NJ and is hybrid (3 days a week onsite)
The Data Architecture and Governance Lead is responsible for designing and implementing data architecture strategies, developing enterprise-wide data models, and establishing governance policies. This role collaborates with stakeholders to create innovative data solutions, ensures data quality and security, and maintains regulatory compliance. The ideal candidate will have extensive experience in data management tools, data quality assurance, and data governance. They will also mentor team members and stay ahead of emerging technologies in the field.
Key Responsibilities:
- Design and maintain data models aligned with business requirements and system architectures.
- Ensure data quality by developing and enforcing standards, validation processes, and metadata management.
- Design and implement data integration architectures, collaborating with ETL developers for seamless data flow.
- Develop and implement a comprehensive data governance framework, including policies, procedures, and standards.
- Establish data governance roles and responsibilities across the organization.
- Create and implement data policies related to data access, security, privacy, retention, and compliance with regulations.
- Define and maintain data architecture principles to ensure consistency and scalability.
- Promote data literacy by creating training programs and fostering a data-driven culture.
- Monitor compliance with data governance policies and conduct regular audits.
- Collaborate with cross-functional teams, communicate progress to senior management, and advocate for data governance best practices.
Key Requirements:
- MS in Computer Science or a related field.
- 5+ years of experience in data architecture , modeling, data governance, or related fields.
- Expertise in data modeling, data integration, and data warehousing.
- Experience with data governance frameworks, policies, and procedures.
- Proficiency in database management systems (e.g., Oracle, SQL Server, PostgreSQL).
- Experience with data modeling tools (e.g., ER/Studio, PowerDesigner, Erwin).
- Knowledge of big data technologies (e.g., Hadoop, MongoDB).
- Familiarity with cloud-based data platforms (e.g., AWS, Azure).
- Understanding of machine learning and AI concepts related to data modeling.
- Proficiency in data visualization tools (e.g., Tableau, Power BI).
- Strong project management, organizational, and collaboration skills.
- Continuous learning mindset and adaptability to evolving data environments.
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