Principal Software Engineer, Data Products

Office / UsRemotefull-timelead

Software EngineerSoftware Engineering

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Quick Summary

Key Responsibilities

Own technical direction and delivery. Define the architecture and implementation approach for a significant area of Fetch’s off-platform data business.

Technical Tools

Software EngineerSoftware Engineering

Meet Fetch Engineering

At Fetch, engineering is driven by curiosity, ownership, and a bias toward action. We operate in complex problem spaces where the right answer is not always clear, and success depends on adaptability, critical thinking, and informed decision-making. Our engineers are comfortable navigating ambiguity, understanding tradeoffs, gathering context, and turning uncertainty into progress while maintaining high technical standards.

Engineers at Fetch take pride in building reliable, scalable systems that serve millions of users. You will contribute directly to the codebase, collaborate closely with cross-functional partners, and help shape best practices that elevate the quality of our work. We foster a culture of mentorship and collaboration, where engineers grow by learning from one another and holding a high bar for quality, reliability, and impact.

About the Role:

Fetch is expanding its data business to help brands understand what consumers buy, reach relevant shoppers, and measure whether advertising drives incremental purchases. We’re hiring a technical leader to build the software behind these products, from creating and delivering audiences to running repeatable measurement workflows. You’ll help turn early capabilities into products that partners can evaluate, integrate, and use at scale.

This is a Principal-level individual contributor role on the software engineering ladder within our Data organization, reporting to the VP of Data. You’ll combine hands-on software development with architectural ownership and technical leadership, guiding a significant product or platform domain from early exploration through production.

You’ll work closely with Engineering, Data Science, Product, and our go-to-market teams to determine what to build, validate it with partners, and establish the systems needed to support a growing business. You’ll tackle problems such as turning a purchase-based audience into a repeatable creation, scoring, and delivery workflow; building measurement pipelines that produce reproducible partner results; and making new partner integrations faster through reusable services and APIs. We’ll agree on your initial area of ownership during the interview process, based on business priorities and your experience

This is a full-time role that can be held from one of our US offices or remotely in the United States.

What you’ll do at Fetch:

Own technical direction and delivery. Define the architecture and implementation approach for a significant area of Fetch’s off-platform data business. Lead work from problem definition and proof of concept through production delivery and ongoing improvement.
Build and operate production software. Design, implement, and maintain the services, APIs, and processing workflows behind our data products. Work with Core Data Platform to build on shared ingestion, storage, orchestration, and trusted data assets. Establish clear interfaces and ownership so product teams can extend these capabilities without duplicating foundational infrastructure
Turn evolving needs into concrete solutions. Partner with Product, Sales, and external partners to clarify requirements, test assumptions, and translate feedback into practical engineering decisions.
Make sound architectural tradeoffs. Balance delivery speed, scalability, reliability, and maintainability, choosing solutions appropriate to the product’s stage and partner commitments.
Bring data science into production. Partner with data scientists to turn audience models and measurement methods into reliable software. Build repeatable data preparation, scoring, evaluation, and delivery workflows, with clear versioning, monitoring, and recovery mechanisms. Jointly define production acceptance criteria, balancing scientific validity, partner requirements, runtime, and cost.
Improve data quality and reliability. Build validation, monitoring, and operational safeguards that help ensure accurate, dependable outputs and meet agreed partner service levels.
Lead through technical influence. Align engineers and cross-functional partners on design decisions, resolve dependencies, and guide implementation across the teams contributing to your domain.
Raise the engineering bar. Mentor engineers, provide thoughtful design and code reviews, and establish patterns that help a growing team build and operate these systems effectively.

Minimum Requirements:

15+ years of software engineering experience, including setting technical strategy, leading architectural decisions across organizations, and driving initiatives with company-level impact.
Demonstrated ownership of a data-intensive product from an ambiguous problem or prototype through production launch and sustained customer or partner use. You can explain the architectural decisions you made, what changed after launch, and how you measured reliability, adoption, and business value
A track record of building and operating production software, with direct ownership of consequential architectural decisions and delivery outcomes.
Experience building advertising platforms, audience products, measurement or attribution systems, demand-side platforms, or closely related data products.
Strong software engineering fundamentals, including system design, backend development, testing, and production operations.
Experience designing systems that process substantial volumes of data, with an understanding of data quality, performance, reliability, and operational tradeoffs.
Demonstrated technical leadership of complex initiatives involving multiple engineers or teams, including setting direction, guiding implementation, and resolving technical disagreements.
The ability to move work forward when requirements are incomplete, form informed technical opinions, and adjust your approach as new evidence emerges.
Strong product judgment and the ability to connect technical decisions to partner needs, product adoption, and business outcomes.
Clear communication with technical and nontechnical stakeholders, including the ability to explain trade-offs and challenge requirements constructively.

Preferred Requirements:

Experience bringing machine learning models into production in partnership with Data Science.
Familiarity with audience expansion, lookalike modeling, or predictive systems used in advertising.
Knowledge of statistics, anomaly detection, or techniques for identifying and addressing data quality issues.
Experience integrating data products with advertising platforms or external partners.

Compensation: At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire. Discover our benefits and how our employees live rewarded at https://fetch.com/careers.