Manager, Solution Engineering Informatica Data Foundations - FINS

Salesforce; San Francisco (CA); On-site; USD 155,190 - 207,620; Full time

Job summary

Salesforce is hiring a Manager of Solution Engineering to lead a team that translates complex enterprise data into AI strategies. This role involves coaching technical talent and driving executive alignment to optimize decision-making in a business context.

Experience with data management, modern architectures, and consultative selling is essential. The position offers a competitive salary range of $155,190 - $207,620 annually, with additional bonuses and benefits.

Qualifications

• Strong technical foundation with leadership ambitions.
• Understanding enterprise data management for AI and transformation.
• Coaching others on modern data architectures' impact.

Responsibilities

• Lead and develop a team of Solution Engineers.
• Drive executive alignment with key decision makers.
• Orchestrate complex deals and maintain progress.
• Coach teams on multi-ecosystem architectures.

Skills

Technical foundation for leadership

Enterprise data management and integration

Modern data architectures

Consultative selling approaches

Managing SE capacity

Education

Degree in Computer Science (B.S., Master's, or Ph.D.)

Tools

Salesforce Data Cloud

Informatica

MuleSoft

Job description

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.

The Manager of Solution Engineering is responsible for building, coaching, and scaling a team that translates complex enterprise data environments into clear, outcome‑driven AI strategies for customers. You will drive a Data First strategy, ensuring the team can clearly articulate why a trusted, governed data foundation across fragmented ecosystems is required to operationalize AI.

Responsibilities

• Lead and develop technical talent: guide and coach a team of Solution Engineers across experience levels, building a culture of accountability, preparation, and continuous improvement.
• Drive executive alignment: coach the team to identify and align to the priorities of key decision makers and influencers, moving beyond feature-level discussions into business outcomes, architectural tradeoffs, and risk.
• Orchestrate complex deals: develop the team’s ability to plan ahead, prioritize effectively, and coordinate across stakeholders, reinforcing disciplined deal strategy and maintaining progress without constant manager intervention.
• Elevate the architectural narrative: coach the team to position multi‑ecosystem architectures that unify fragmented data estates into a trusted foundation for enterprise AI, pushing beyond feature-function positioning into outcome‑driven architectural thinking.
• Enforce value discipline and project monitoring: build and reinforce a structured approach to discovery, value validation, and follow‑through, coaching the team to proactively identify risks, address obstacles early, and tie technical engagement to measurable business impact.
• Balance coaching vs. direct involvement: demonstrate sound judgment about when to step into deals versus coaching from the sidelines, with a bias toward developing team capability over individual contribution.

Qualifications

• Strong technical foundation with the ability and desire to grow into a leadership role focused on coaching and scaling others.
• Strong understanding of enterprise data management and integration, with the ability to coach others on how these capabilities enable AI, automation, and digital transformation.
• Experience with modern data architectures, including cloud data platforms, integration patterns, and the role of data in supporting Generative AI and Large Language Models.
• Demonstrated ability to coach consultative and value‑based selling approaches, connecting technical solutions to measurable business outcomes.
• Experience managing or supporting SE capacity, deal prioritization, and pipeline execution within a technical sales environment.
• Degree in Computer Science required (B.S., Master’s, or Ph.D.).

Preferred Qualifications

• Leadership experience: 5+ years in technical pre‑sales, strategy, or management consulting, with clear evidence of leadership through mentoring, informal team leadership, or driving initiatives in complex sales environments.
• Enterprise platform knowledge: experience with platforms such as Salesforce Data Cloud, Informatica, MuleSoft, or similar, and an understanding of how to position across heterogeneous ecosystems to deliver a unified data foundation.
• FINS domain knowledge: experience in Financial Services, including familiarity with regulatory constraints, data fragmentation challenges, and enterprise data modernization efforts.

Compensation

The typical base salary range for this position is $155,190 - $207,620 annually. In California and New York, and select cities in the metropolitan areas of Boston, Chicago, Seattle, and Washington DC, the base pay range is $170,660 - $228,340 per year. The range represents base salary only and does not include company bonus, incentive for sales roles, equity, or benefits, as applicable.

Equal Opportunity Employer

Salesforce is an equal opportunity employer and maintains a policy of non‑discrimination with all employees and applicants for employment. Any employee or potential employee will be assessed on the basis of merit, competence, and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. Recruiting, hiring, and promotion decisions are fair and based on merit.