Mqreferrals
VP, Total Rewards
Remote, USA · Vp
Sponsorship not specified$282k-$353kDetected 27 days ago
CompensationLeadershipCommunicationCollaborationMentoring
About the role
- As Marqeta's VP, Total Rewards you will play a pivotal role in shaping and executing the company's global total rewards strategy.
- This role can be performed remotely anywhere within the United States or from our Oakland office.
- Your Manager - Helena Christianson, Chief People Officer Typical Process - Application Submission - Recruiter video call - Hiring manager video call - Virtual "Onsite" consisting of 4-5, 45 min calls - Offer!
Responsibilities
- Partner with Finance and Legal teams to ensure compliance with all relevant regulations and governance requirements, particularly regarding executive compensation.
- Excellent communication and interpersonal skills, with the ability to influence and collaborate effectively across all levels of the organization.
Requirements
- Strong understanding of executive compensation principles, including experience interfacing with the Compensation Committee of the Board of Directors.
Nice to have
- A tier for the most expensive working areas, like the San Francisco Bay area and New York City.
- Visit this page or consult with a Recruiter to determine which tier would be applicable to you.
- Free therapy sessions, financial and professional coaching, and legal advice
- Through Flex First, the freedom to live and work wherever you and your family thrive
- Premium Plus: A tier for the most expensive working areas, like the San Francisco Bay area and New York City.
- Premium Plus: $298,000- $372,500
Compensation
- Marqeta is a Flex First company which allows you to choose your best working environment, whether that be from home or at a company office.
- To support Flex First, we calibrate pay to a competitive value according to working location.
- is aligned according to three tiers within the
- Annual "development dollars" to support our people growth and development
Benefits
- Evolve and expand our total rewards strategy globally, ensuring that we attract, retain, and motivate our distributed teams.
- Lead the global design, implementation, and administration of competitive compensation programs, including base pay, variable pay, and equity incentives.
- Oversee the management of our employee benefits programs, ensuring they are competitive, cost-effective, and aligned with employee needs and company objectives.
- Conduct regular benchmarking and analysis to ensure our total rewards programs remain competitive in the market and support our talent acquisition and retention efforts.
- Provide strategic guidance and recommendations to the Executive Leadership Team and the Compensation Committee of the Board of Directors on total rewards matters.
- In partnership with Legal and other internal People functions, ensure overall equity and diversity compliance globally.
- Drive continuous improvement and innovation in our total rewards programs, leveraging technology and best practices to enhance efficiency and effectiveness.
- Lead, coach and develop a high-performing team of compensation and benefits professionals, fostering a culture of collaboration, accountability, and continuous learning, further developing future leaders.
- 10+ years of experience in total rewards, compensation, and benefits management, with further experience in a leadership role.
- Demonstrated expertise in designing and implementing global compensation and benefits programs within the tech industry, ideally in both large established organizations and growth companies.
- Strategic mindset with the ability to think analytically and translate business objectives into effective total rewards strategies.
- Multiple health insurance options
- Monthly stipend to support our remote work model
Equal opportunity
- Manage EEO/AA compliance to include preparation, enforcement, and communication of Affirmative Action Plans and programs and timely required filings such as EEO-1 and Vets-100.
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This listing is sourced directly from Mqreferrals's careers page and normalized into a canonical job model.