Senior Manager, Solutions Engineering

Fetch•Remote,

About The Position

AI & Data at Fetch sit at the center of how we understand our business, make decisions, and build intelligent products. The organization operates as an integrated AI & data ecosystem, spanning multiple disciplines, including data engineering, analytics engineering, machine learning, experimentation, and data platforms, all working together to turn data into durable business and customer impact. Teams operate in complex problem spaces where requirements evolve, tradeoffs are constant, and the right answer is rarely obvious. Success depends on strong technical judgment, comfort with ambiguity, and the ability to gather context and make informed decisions while balancing quality, performance, scalability, and responsible use. Practitioners across this org contribute hands-on to production systems, analytical foundations, and intelligent features. You will collaborate closely with product, platform, and engineering partners, help shape standards and best practices, and ensure our AI and data capabilities scale reliably as Fetch grows. Fetch is looking for a Senior Manager, Solutions Engineering, to lead a multidisciplinary team of Solutions Engineers, Analytics Engineers, and Data Engineers. This team delivers client-facing technical solutions that connect client needs, product strategy, data insights, engineering execution, and business outcomes. This leader will own measurable outcomes across solution delivery, analytics quality, data reliability, product progress, and client impact. The ideal candidate is strong in analytics and data engineering, energized by client-facing work, and able to translate ambiguous client, product, and technical needs into clear roadmaps, scalable solutions, and durable operating practices. The Senior Manager will lead technical talent across solution design, data modeling, analytics quality, systems thinking, and delivery execution. They will partner closely with Product, Engineering, Go-to-Market, Client Success, Analytics, and Data teams to align priorities, resolve dependencies, and ensure solutions are client-ready, analytically sound, scalable, reliable, and maintainable.

Requirements

6+ years of experience in solutions engineering, analytics engineering, data engineering, software engineering, platform engineering, technical implementation, or a related technical discipline.
2+ years of technical team management experience, including direct people management of solutions engineers, analytics engineers, data engineers, software engineers, or technical solution owners.
Experience leading teams responsible for client-facing technical solutions, analytics deliverables, data products, integrations, platforms, or product engineering outcomes.
Proven ability to translate strategy into roadmaps, execution plans, measurable outcomes, and sustainable operating rhythms.
Strong technical judgment across analytics, data modeling, data pipelines, architecture, integration design, scalability, reliability, maintainability, observability, and operational risk.
Track record of balancing client or product delivery with data quality, technical debt, reliability, analytical rigor, and long-term system health.
Experience coaching senior engineers or technical leads in ownership, design quality, decision-making, and cross-functional influence.
Demonstrated ability to influence peer managers and cross-functional stakeholders without relying solely on authority.
Strong communication skills with the ability to explain technical, analytical, and data trade-offs to technical, non-technical, and client-facing audiences.

Nice To Haves

Experience managing multiple related workstreams, teams, or technical domains.
Experience in client-facing, analytics, data, platform, integration, ad tech, martech, marketplace, consumer product, or high-scale distributed systems environments.
Experience improving engineering or analytics productivity through better planning, review practices, tooling, automation, quality gates, observability, or developer experience.
Experience establishing team or org-level technical standards, architectural principles, design review mechanisms, incident practices, or system ownership models.
Experience partnering closely with Product, Go-to-Market, Client Success, Sales Engineering, Analytics, Data, or Operations teams.
Experience leading through ambiguity, organizational change, or high-pressure delivery environments.
Practical fluency with AI-assisted engineering, analytics, or productivity tools, including thoughtful judgment around use cases, risks, validation, data accuracy, and team adoption.

Responsibilities

Own measurable outcomes across technical delivery, analytics quality, data reliability, solution quality, product progress, and client impact.
Translate client needs, analytics opportunities, product strategy, and technical strategy into a measurable quarterly and annual roadmap.
Balance near-term delivery with reliability, scalability, developer experience, data quality, and technical debt reduction.
Ensure trade-offs between speed, quality, scope, and long-term maintainability are clearly understood and aligned across stakeholders.
Own a business-critical client-facing solution domain, analytics/data product area, or technical system, including its scalability, reliability, data quality, and maintainability.
Guide teams toward sound technical and analytical decisions that balance speed, scalability, data integrity, and client impact.
Identify emerging technical, analytical, and data risks before they constrain delivery, client trust, reliability, or team productivity.
Raise the technical and analytical bar through stronger design reviews, data quality expectations, system ownership norms, and solution review practices.
Establish engineering, analytics, and data processes that create consistently high solution quality and trustworthy insights.
Convert ambiguous client, business, product, data, and technical needs into execution plans with clear owners, milestones, and measurable outcomes.
Lead cross-team initiatives that improve reliability, developer experience, delivery effectiveness, integration quality, or solution scalability.
Drive execution beyond the immediate team by aligning dependencies, clarifying ownership, and resolving misalignment across partner teams.
Use data and context, including incidents, velocity, quality metrics, roadmap progress, client impact, and technical health trends, to shape prioritization and decision-making.
Build sustainable team operating rhythms that reinforce accountability for outcomes, not activity.
Lead, coach, and develop Solutions Engineers, Analytics Engineers, Data Engineers, and technical leads across delivery, technical judgment, systems thinking, design quality, and ownership.
Develop senior ICs into stronger technical owners and decision-makers.
Ensure consistent performance management, clear expectations, and timely feedback across the team.
Proactively identify team health patterns, including retention risks, disengagement, workload imbalance, unclear ownership, or structural causes of friction.
Maintain a sustainable operating environment by balancing delivery pressure with technical investment and team capacity.
Partner with Product, Engineering, Analytics, Data, Go-to-Market, Client Success, and peer leaders to align on shared goals, dependencies, and delivery trade-offs.
Advocate for solutions that improve client outcomes, system quality, data reliability, and long-term maintainability.
Communicate technical direction, analytical insights, data risks, and delivery trade-offs clearly to technical, non-technical, and client-facing audiences.
Model constructive conflict resolution and create psychological safety during high-pressure delivery moments.
Institutionalize technical standards, operating principles, and decision-making mechanisms that improve consistency across the organization.