Fetch

Compensation

Full Description

Meet Fetch AI & Data 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. About the role: Fetch is at a critical inflection point in how data is produced, moved, and operationalized across the company. With millions of monthly active users, real-time user interactions, and increasing investment in AI-driven and data-powered products like FetchGPT, the reliability, scalability, and correctness of our data platforms are foundational to every decision and product we ship. We are seeking a Manager, Data Platforms to own and operate Fetch’s core data platform capabilities outside of the data warehouse itself. This role is responsible for the end-to-end data pipeline and infrastructure that powers analytics, experimentation, machine learning, real-time use cases, and downstream applications. You will lead the team that designs, builds, and operates ingestion systems, streaming and batch pipelines, data processing frameworks, and the infrastructure that makes data trustworthy and available at scale. This role requires strong technical judgment, systems thinking, and disciplined execution. You will be expected to sequence work thoughtfully, balance near-term delivery with long-term platform health, and guide the organization toward scalable, well-architected solutions. As the team grows, this role has a clear path to managing managers and owning broader platform strategy. Within your first year, you will stabilize and mature Fetch’s core data pipelines, establish clear platform ownership boundaries and operating standards, and deliver a phased roadmap that enables real-time and batch data products to scale reliably with the business. What You’ll Do at Fetch: Data Platform Ownership and Strategy Own Fetch’s core data platform, covering data ingestion, batch and streaming pipelines, real-time infrastructure, and supporting services outside of the warehouse. Define and evolve the platform architecture that supports analytics, experimentation, ML, and product use cases. Establish a clear technical vision and phased roadmap for data platform evolution. Balance innovation with operational stability, ensuring the platform scales with business growth. Pipeline and Infrastructure Leadership Lead the design and operation of high-volume, reliable batch and real-time data pipelines. Own infrastructure that supports streaming use cases, near-real-time analytics, and data availability SLAs. Partner with Infrastructure, Product Engineering, Analytics Engineering, and ML teams to ensure platform capabilities align with downstream needs. Ensure systems are observable, resilient, and cost-aware. Technical Execution and Design Quality Set a high bar for system design, code quality, and operational excellence. Guide the team through software design lifecycles, including requirements definition, technical design, phased delivery, and deprecation. Make pragmatic architectural decisions, knowing when to invest and when to constrain scope. Hold eager development in check to ensure work is sequenced and delivered in the right order. Team Leadership and Growth Manage and mentor data platform engineers, providing technical guidance and career development. Act as a hands-on technical leader, especially for complex or high-risk systems. Build a strong team culture centered on ownership, reliability, and craftsmanship. Prepare the organization for future growth, with the potential to manage managers as the platform organization expands. Platform Governance and Reliability Define standards for data pipeline reliability, SLAs, and operational ownership. Establish incident response, on-call practices, and postmortem culture for data systems. Improve platform documentation, onboarding, and internal developer experience. Ensure platform changes are communicated clearly and adopted safely across teams. Minimum Qualifications 10+ years of experience in data engineering, platform engineering, or infrastructure-focused software engineering, with meaningful experience managing engineers. Demonstrated success leading and scaling engineering teams, including ownership of hiring, performance management, career development, and team health. Proven ability to set technical direction through others, balancing hands-on technical depth with effective delegation. Experience owning large, business-critical platforms with uptime, reliability, and delivery accountability. Strong track record of planning, sequencing, and executing multi-quarter technical initiatives, including managing scope, dependencies, and stakeholder expectations. Ability to operate effectively in ambiguous environments, providing structure, prioritization, and clear decision-making. Bachelor’s degree in Computer Science, Engineering, or a related technical field. Preferred Qualifications Experience managing multiple teams or first-line managers, or clear readiness to grow into that scope as the organization scales. Background leading platform or infrastructure teams at large-scale or highly technical organizations (e.g., Google, Amazon, or similar). Demonstrated strength in organizational design, including defining ownership boundaries, team interfaces, and operating models. Experience driving platform governance, including reliability standards, SLAs, incident management, and postmortem processes. Strong cross-functional leadership skills, with a history of partnering effectively with Product, Infrastructure, Analytics, and ML leadership. Ability to develop future leaders, including mentoring senior engineers into technical leads and managers.