Data Lead
 

The Data Lead provides high-level creative vision for a suite of digital products used by individual investors, retirement plan administrators, and internal associates. They oversee data-related processes, ensuring efficient data collection, quality, and security. This role plays a critical part in maintaining data integrity and accessibility across the organization1.

 Responsibilities:

• Create complex queries and list pulls for direct marketing campaigns to prospects and customers.
• Facilitate the management of the direct marketing calendar for the Americas.
• Assist technology, systems, and process workstreams in defining the common data model vision, data sourcing approach, transformation approach, and reconciliation approach.
• Produce global load specifications and carry out data loading.
• Plan and oversee day-to-day workstream/team operations and milestone delivery.
• Manage the team’s budget.
• Be accountable for on-time delivery of program outcomes and agreed benefits within the budget.
• Define program outcomes and business cases, aligning them with strategic objectives.
• Direct several other Program Managers.

Qualifications and Requirements:

Required Qualifications:

• Bachelor’s or Master’s Degree in Computer Science, Statistics, Engineering, Education, Mathematics, Business, Economics, Science, Management, or Finance.
• Relevant certifications such as AWS, ITIL, CISSP, MCTS, PMP, CISA, GIAC, MCSE, CCSP, or CCNP.
• 8 to 12 years of experience in data management and analytics.

Preferred Qualifications:

• Expert knowledge of data modeling techniques.
• Experience conducting reviews to ensure quality, standards compliance, reusability, and ease of maintenance.
• Ability to document, prioritize, and update data quality-related issues.
• Familiarity with implementing MDM solutions.
• Minimum of 10 years of experience working as a Data Architect.

Skills and Competencies:

• Strong leadership and strategic thinking.
• Proficiency in data governance and compliance.
• Excellent communication and collaboration skills.
• Technical acumen in data analytics and visualization.
• Problem-solving abilities and attention to detail.