Data Governance & Quality Team Manager

As the Data Governance & Quality Team Manager, you will oversee a team of data stewards/architects and play a crucial role in designing and implementing our data governance & quality strategy. Your expertise will be key in ensuring that our data is organized, accessible, and secure, allowing us to make data-driven decisions and drive business success. We are looking for a driven and knowledgeable individual who possesses strong leadership skills and a deep understanding of data architecture principles and tools. Here are some key responsibilities for the Data Governance & Quality Team Manager:

• Team Leadership: Manage and provide leadership to a team of data stewards/architects, ensuring effective collaboration and coordination among team members. Set clear goals, provide guidance and mentorship, and evaluate individual and team performance.
• Data Quality: Develop and maintain a robust data quality strategy & roadmap that aligns with the organization's overall business objectives. This includes importing data models, defining meta data standards, and ensuring data integrity, security, quality, profiling & sampling.
• Data Governance: Advance data governance policies, procedures, best practices and ensure compliance throughout the organization. Collaborate with stakeholders (data stewards, data governance council, etc.) to define data standards, data classification, data retention, data lifecycle management and advance data catalog usage.
• Data Integration & Marketplace: Oversee the design of data integration processes, ensuring seamless data flow and interoperability between systems and marketplace. Work closely with data engineering & architecture team to ensure effective data & metadata integration and transformation.
• Data Security and Privacy: Ensure the implementation of data security and privacy measures, in compliance with relevant regulations (such as GDPR, HIPAA, etc.), to protect sensitive data from unauthorized access or breaches.
• Data Analytics and Reporting: Collaborate with business analysts and data scientists to define data requirements for analytics and reporting purposes. Oversee and support the design of data analytics platforms, data warehouses, and reporting solutions.
• Stakeholder Engagement: Engage with business & legal stakeholders - including executives, managers, and end-users, to understand their data needs and provide strategic recommendations. Collaborate with cross-functional teams to define and execute data-driven initiatives.
• Vendor Management: Evaluate and select third-party vendors or solutions for data-related products or services. Manage vendor relationships, contracts, and service level agreements (SLAs) to ensure successful delivery.
• Continuous Improvement: Stay updated with emerging data management trends, technologies, and best practices. Identify opportunities for process improvement, automation, and optimization within the data architecture team.
• Collaboration and Communication: Foster a culture of collaboration, knowledge sharing, and effectivecommunication within the team and across departments. Facilitate regular team meetings, workshops, and training sessions to enhance technical skills and foster innovation.

• Work together with Unit and Dept leadership to develop and deliver long-term strategic goals for data architecture roadmaps; sense, study, test and implement new technologies and manage overall data knowledge.
• Build, lead and manage high performance team of data stewards/architects to meet organizational data strategy and deliver project with quality and customer service focus. Foster associate development by coaching, training, and mentoring.
• Establish and lead enterprise information governance methods, stewardship and procedures for tracking data quality, completeness, redundancy, and improvement. Develop and promote cloud data strategy.
• Build NA & global relationships and network to achieve trust and credibility, by discovering and meeting the needs of internal and external customers and vendors. Use persuasion and influence to achieve maximum results with Enterprise IT goals.

Hybrid: At least 3 days per workweek at Torrance, CA

This position is not eligible for work visa sponsorship.

Education:College degree in computer science, information systems, or computer engineering

Other qualifying requirements:

• 8 or more years of progressive experience in data management leading teams as a data or information architect
• 8 or more of experience leading architecture/stewardship teams in Data Analysis, Metadata management, Information Management and Business Intelligence
• 8 or more of advance knowledge of designing & working with multi-dimensional, mining transactional data and strategies that drive business.
• Strong experience with tools such as Erwin, Informatica Data Catalog, Glue Data Catalog, etc.
• Hands-on experience with data modeling, metadata management, data mining, large-scale data modeling, and business requirements gathering/analysis
• Knowledgeable, go-getter, self-driven individual with strong sense of ownership.
• Team player/collaborator who builds relation with customers and team members, earns their trust, and creates influence to meet tactical or strategic objectives.
• Servant leader who clears roadblocks for the team members to meet their deliveries and help them grow individually.
• Knowledge of project management, budgeting, financial management, vendor management, service management and operational efficiency will be a huge plus.
• Strong oral, verbal communication/presentation skills.
• Strong understanding of relational data structures, theories, and principles. Experience with database platforms, including DB2, MS SQL Server, PostgreSQL, Couchbase, MongoDB, etc.
• Experience in enterprise information life cycle management including enterprise repository tools, data modeling, mapping, profiling, quality and master data management practices.
• Experience with data catalog, metadata management, and data discoverability.
• Knowledge of cloud-based technology including cloud connectivity options, data storage options (S3, Glarcier), data lakes (S3 etc.), cloud warehouses (Redshift, etc.), cloud ETL/ELT tools, cloud streaming options (Kinesis, Kafka etc.), cloud databases (RDS, DynamoDB etc.), data search options and cloud/on-prem BI products (Power BI, Tableau, etc.).
• Working knowledge of Big Data platforms technologies and processes including cloud big data products like EMR etc.