> Markdown version of [/jobs/ext/4550893-software-engineer-customer-studio-backend](https://www.wearedevelopers.com/jobs/ext/4550893-software-engineer-customer-studio-backend). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer, Customer Studio Backend - **Company:** Recruiting from Scratch - **Location:** San Francisco, CA, United States (Remote available) - **Salary:** $180,000.0 - $320,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Databases, Customer Data Management, Extract Transform Load (ETL), Data Warehousing, Distributed Systems, Query Optimization, Software Engineering, SQL Databases, Systems Architecture, Data Processing, Generative AI, Change Data Capture, Backend, Stream Processing - **Published:** November 3, 2026 - **Apply:** https://www.careerbuilder.com/job-details/software-engineer-customer-studio-backend-san-francisco-ca--881c40b2-196c-43b3-93b8-06bd7d268a14 ## About the Role Software Engineering, Software Engineering, Funding, ISO (International Organization for Standardization), Data Warehousing, Business Operations, Customer/Client Research, Marketing, Database Extract Transform and Load (ETL), Artificial Intelligence (AI), * Senior-level software engineer with strong backend engineering fundamentals. * Demonstrated experience building and evolving production backend systems. * Experience with distributed systems, system architecture, scalability, maintainability, and reliability. * Evidence of owning complex projects from design through implementation and production. * Strong product mindset, including the ability to understand customer needs and make sound technical trade-offs. * Comfortable engaging with product specifications and contributing to problem definition. * Years of experience are not the primary selection criterion; demonstrated impact, technical depth, and potential for growth matter more. Technical Requirements * Strong backend engineering and distributed systems experience. * Ability to design scalable, reliable, maintainable, and extensible software. * Experience reasoning about data-intensive systems and performance challenges. * Strong architectural judgment and ability to solve complex technical problems from first principles. * Experience building systems that serve customer-facing product workflows. * Ability to work on systems involving data warehouses, audience computation, syncing, or real-time data processing. Product and Customer Thinking * Understands how technical decisions affect customer outcomes and product usability. * Can translate ambiguous customer problems into practical technical solutions. * Comfortable discussing product specifications and helping shape the solution. * Balances technical quality with speed, simplicity, and business impact. * Takes ownership of outcomes rather than focusing only on implementation details. Ownership and Execution * Can lead projects independently from problem definition through delivery. * Makes thoughtful decisions about architecture, reliability, and future maintainability. * Proactively identifies performance bottlenecks and opportunities for improvement. * Works effectively in a fast-moving environment with substantial autonomy. * Shows persistence and intellectual curiosity when solving difficult problems. Communication and Collaboration * Strong written and verbal communication. * Comfortable collaborating with product and engineering partners. * Able to explain technical trade-offs clearly. * Works with compassion and kindness while maintaining a high engineering bar. * Demonstrates a growth mindset and responds constructively to feedback., * Experience with data warehouses and warehouse query optimization. * Experience with Reverse ETL, customer data platforms, data activation, or marketing technology. * Experience with real-time data processing, change data capture (CDC), and audience syncing. * Experience with analytics, experimentation, or audience segmentation. * Experience with low-latency APIs, caching layers, or high-throughput distributed systems. * Experience applying generative AI to customer-facing product workflows. * Experience building infrastructure or core backend systems from scratch. ## Description * Design, build, and maintain backend systems for a no-code product that enables customers to activate warehouse data without needing to write SQL. * Develop features that help users create audience segments, decide which data to sync, and activate data across downstream platforms. * Own projects from initial problem definition through architecture, implementation, deployment, and ongoing improvement. * Work closely with product and other engineering teams to turn customer needs into reliable, scalable solutions. 2. Solve Data Warehouse Performance Challenges * Improve the speed, performance, and interactivity of warehouse-powered products. * Investigate and implement query optimizations, precomputed state, and other performance improvements. * Explore warehouse-specific optimizations to improve customer workflows. * Design systems that remain maintainable and reliable as customer data volumes and usage grow. 3. Build Analytics and Experimentation Capabilities * Develop systems that help customers understand and evaluate audience segments. * Build features that support experimentation with downstream tools. * Enable customers to track the performance of different audiences and use data to make better decisions. * Help shape the architecture behind analytics and experimentation workflows. 4. Develop Real-Time Audience Syncing * Explore ways to make data syncing faster and keep customer data fresher. * Work on real-time audience computation and syncing as data warehouses increasingly adopt change data capture (CDC) and other real-time technologies. * Build reliable backend systems that support low-latency, high-throughput data processing. 5. Explore Generative AI Applications * Contribute to making data activation workflows more seamless through generative AI. * Identify opportunities to improve user experiences and reduce friction in working with data. * Build practical AI-powered capabilities that solve real customer problems. 6. Own Architecture, Scalability, and Reliability * Make thoughtful architectural decisions across backend systems and distributed services. * Consider scalability, maintainability, reliability, and simplicity when designing solutions. * Build and evolve core systems rather than relying solely on off-the-shelf components. * Take responsibility for the long-term quality and extensibility of the systems you develop. 7. Collaborate With Product and Customers * Engage with product specifications and contribute to defining solutions before implementation begins. * Bring strong customer and product thinking to technical decisions. * Work directly with customers on difficult scaling problems when needed. * Communicate clearly across engineering and product teams, and take ownership of outcomes rather than only completing assigned tasks.