Jobs at Northbeam

Own an enterprise customer portfolio, supporting onboarding, product integrations, troubleshooting, account health monitoring, retention, and expansion. Coordinate with Product, Engineering, Support, Onboarding, and Media Strategy teams to resolve issues, deliver recurring insights, manage feedback, and improve customer engagement. Use analytics and CRM tools to identify risks, automate health tracking, and help customers maximize Northbeam’s marketing intelligence platform.

Advise eCommerce clients on media buying, budget allocation, creative strategy, attribution, and growth frameworks across paid channels. Conduct data reviews and growth audits, translate attribution and MMM insights into recommendations, support onboarding and retention, and develop repeatable reporting and benchmarking playbooks. Collaborate with Product, Marketing, and Customer Success teams to communicate customer needs and improve the platform.

Own major fullstack product features from design through launch using TypeScript, React, REST, GraphQL, SQL, and BigQuery. Lead complex, high-impact projects, influence technical direction, collaborate with product and customer teams, optimize dashboard performance, deliver scalable software, document systems, and mentor engineers.

Design high-fidelity visual experiences for a data-heavy B2B SaaS platform across web, mobile, email, and integrations. Improve typography, color, layout, information density, data visualization, and overall product quality. Build and extend the design system, translate rough concepts into polished designs, and collaborate with product, engineering, data science, media strategy, brand, marketing, customers, and executives. This is a hands-on individual contributor role focused on AI interfaces, incrementality, actionable insights, and complex data platforms.

Applied Data Scientist focused on incrementality, causal inference, experimentation, Marketing Mix Modeling, and predictive products. The role partners directly with customers to interpret data, diagnose measurement issues, explain statistical results, and provide actionable recommendations. Responsibilities include building diagnostic tools, analyzing model and experiment outcomes, improving methodologies and production capabilities, and collaborating with Product, Engineering, Media Strategy, Customer Success, and senior data scientists.

Own end-to-end technical onboarding for new customers, including product configuration, permissions, workflows, API integrations, data migration, troubleshooting, and go-live. Manage implementation timelines, milestones, risks, and deliverables while coordinating with customers and internal Sales, Customer Success, Product, Support, and Engineering teams. Contribute to onboarding documentation and playbooks.

Build and maintain reliable data pipelines, APIs, integrations, and event-driven or batch processing systems. Transform data from advertising, ecommerce, order management, and event sources while improving monitoring, freshness, performance, and scalability. Collaborate with data engineering, infrastructure, product, and business teams to extend the integration platform in a cloud-native, multi-tenant environment.

Lead backend-focused software architecture and development across distributed systems, data ingestion, experimentation platforms, AI workflows, and product capabilities. Build primarily in Python while contributing to React and TypeScript frontend work. Translate ambiguous product needs into scalable production systems, guide technical direction, partner with product and data teams, mentor engineers, and improve engineering practices.

Build backend services, APIs, data-processing systems, and frontend features for Northbeam’s marketing intelligence platform. Work on experimentation, near-real-time data infrastructure, AI-powered workflows, data integrations, RBAC, and end-to-end product delivery. Collaborate with data scientists, product managers, designers, and senior engineers while contributing across backend, frontend, pipelines, and infrastructure in a fast-moving environment.

Own the architecture and technical direction of Northbeam’s data ingestion and integration platform. Design scalable API-based ETL, event-driven and batch processing systems; establish standards for observability, freshness, and failure handling; and guide build-versus-buy decisions. Collaborate across engineering, infrastructure, product, and business teams while mentoring engineers, leading design reviews, and driving complex platform initiatives to completion.

Own the technical health of existing customer accounts, including configuration, tracking, integrations, data ingestion, and reporting pipelines. Diagnose data quality issues and technical risks, resolve problems or coordinate escalations, and communicate findings to customer-facing and technical teams. Develop health checks, documentation, and runbooks while identifying recurring issues for standardization and product improvement.

Design, build, and maintain scalable data pipelines and tenant-aware APIs to ingest and transform data from varied sources. Work with event-driven and batch architectures, implement authentication and integration patterns, ensure observability/monitoring, optimize data flows for cost and performance, and collaborate with product, infrastructure, and engineering teams to onboard and maintain data sources at scale.

Design and implement scalable backend and distributed systems for a marketing intelligence platform. Build near-real-time ingestion and processing, scale an incrementality/experimentation product, integrate AI-powered workflows, improve data ingestion/exports and connection-state systems, and contribute frontend components to deliver end-to-end product experiences.

Design, develop, and deliver fullstack web solutions, optimize platforms, mentor engineers, and manage product features from ideation to launch.

Lead development and operationalization of measurement products (MMM, incrementality, insights, recommendations). Build, deploy, and maintain production-grade statistical and ML systems, debug end-to-end data and model issues, evaluate methodologies, and partner with engineering, product, and customer teams to improve measurement accuracy and reliability. Provide customer-facing explanations and support for measurement outputs.