Job description

About DevRev At DevRev, we're building the future of work with Computer – your AI teammate. Unlike traditional tools, Computer unifies all your data sources, tools, and workflows into a single AI-ready platform, giving employees real-time insights, proactive suggestions, and powerful agentic actions. It extends your existing software with AI-native apps and agents that work alongside your teams and customers – updating workflows, coordinating across teams, and eliminating repetitive work. We call this Team Intelligence: human-AI collaboration that breaks down silos, brings people back together, and frees you to solve bigger problems. Backed by Khosla Ventures and Mayfield with $150M+ raised, DevRev is trusted by global companies across industries. About the role We are looking for a Senior Data Engineer to help build and evolve the data platform that powers critical business decisions and customer-facing experiences. You will own significant parts of our data architecture that is main powerhouse of DevRev Computer’s memory for accurate and efficient Answers. As a part of data team, you will design and operate scalable data systems, and work closely with Software Engineering, AI Agent teams, Data Science, and Product teams to turn complex data requirements into reliable, high-quality data products. This role is ideal for an experienced engineer who enjoys solving challenging problems involving large-scale data, distributed systems, database architecture, and performance optimization. You will have significant technical ownership and the opportunity to influence the direction of our agentic data platform while helping raise the engineering bar across the team. Responsibilities Own data architecture for large-scale, high-impact projects, making thoughtful tradeoffs across scalability, reliability, performance, maintainability, and operational cost. Design, build, and operate scalable data pipelines and data systems that reliably ingest, transform, store, and serve large volumes of data. Partner closely with Software Engineering, Data Science, Product Management, and other stakeholders to understand data requirements and translate them into robust technical solutions. Define and own data quality, reliability, and SLA/SLO requirements for datasets and systems within your area of ownership. Design and optimize data models, databases, and complex SQL workloads, with a strong focus on query performance, storage efficiency, and scalability. Build frameworks, tooling, and reusable infrastructure that make it easier for engineers and data consumers to develop and maintain data products. Identify opportunities to leverage data to improve products, customer experiences, and business outcomes, and influence cross-functional teams toward high-impact solutions. Establish and promote engineering best practices around testing, observability, deployment, and operational excellence for data systems. Mentor engineers through technical guidance, design reviews, and actionable feedback, while contributing to a strong engineering culture. Minimum Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. 5+ years of software or data engineering experience building production systems. Strong programming experience in one or more general-purpose languages such as Go, Java, C++, Python, or JavaScript, along with strong SQL skills. Strong understanding of data structures, algorithms, and software engineering fundamentals. Experience designing and operating production-grade data pipelines or distributed data systems. Experience working with relational and/or NoSQL databases and understanding their underlying performance and scalability characteristics. Strong ability to independently drive projects from technical design through implementation, deployment, and operation. Preferred Qualifications Experience designing large-scale data platforms, data warehouses, or distributed data systems. Deep understanding of database architecture, data modeling, query optimization, indexing, partitioning, and storage systems. Experience with cloud data infrastructure and databases, including understanding of performance, scalability, reliability, and cost tradeoffs. Experience building and operating high-throughput or large-scale data pipelines. Experience working with large datasets and optimizing complex SQL queries and data processing workloads. Experience with distributed data technologies such as Kafka, Spark, Flink, Trino/Presto, BigQuery, Snowflake, or similar systems. Strong experience with data quality, observability, monitoring, and production reliability. Experience developing robust testing strategies, including unit, integration, and data quality testing. Experience providing technical mentorship and driving engineering best practices across teams. Master’s degree in Computer Science or a related technical field. How do we work? Whatever your role, our values describe what we ask of each other. Be a bridger Look beyond your own role. Ask questions, share context and help others get unstuck. That may mean bringing the right people together or picking up a problem that doesn’t necessarily fit neatly into your job description. Care loudly We want your perspective, not just your agreement. Speak up when something isn’t working or someone needs support. Give honest feedback with respect for the person receiving it. Don’t let an uncomfortable conversation become an unspoken problem. Own the outcome Take responsibility for the result, not just your part in the process. Use AI to move the work forward, not to outsource your judgment. Make the call, check whether it worked and change course when it didn’t. If something goes wrong, own it and help fix it. That’s DevRev! DevRev is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.

Requirements

Must-haves

Own data architecture for large-scale, high-impact projects, making thoughtful tradeoffs across scalability, reliability, performance, maintainability, and operational cost.
Design, build, and operate scalable data pipelines and data systems that reliably ingest, transform, store, and serve large volumes of data.
Partner closely with Software Engineering, Data Science, Product Management, and other stakeholders to understand data requirements and translate them into robust technical solutions.
Define and own data quality, reliability, and SLA/SLO requirements for datasets and systems within your area of ownership.
Design and optimize data models, databases, and complex SQL workloads, with a strong focus on query performance, storage efficiency, and scalability.
Build frameworks, tooling, and reusable infrastructure that make it easier for engineers and data consumers to develop and maintain data products.
Identify opportunities to leverage data to improve products, customer experiences, and business outcomes, and influence cross-functional teams toward high-impact solutions.
Establish and promote engineering best practices around testing, observability, deployment, and operational excellence for data systems.
Mentor engineers through technical guidance, design reviews, and actionable feedback, while contributing to a strong engineering culture.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
5+ years of software or data engineering experience building production systems.
Strong programming experience in one or more general-purpose languages such as Go, Java, C++, Python, or JavaScript, along with strong SQL skills.
Strong understanding of data structures, algorithms, and software engineering fundamentals.
Experience designing and operating production-grade data pipelines or distributed data systems.

Nice-to-haves

Experience designing large-scale data platforms, data warehouses, or distributed data systems.
Deep understanding of database architecture, data modeling, query optimization, indexing, partitioning, and storage systems.
Experience with cloud data infrastructure and databases, including understanding of performance, scalability, reliability, and cost tradeoffs.
Experience building and operating high-throughput or large-scale data pipelines.
Experience working with large datasets and optimizing complex SQL queries and data processing workloads.
Experience with distributed data technologies such as Kafka, Spark, Flink, Trino/Presto, BigQuery, Snowflake, or similar systems.
Strong experience with data quality, observability, monitoring, and production reliability.
Experience developing robust testing strategies, including unit, integration, and data quality testing.
Experience providing technical mentorship and driving engineering best practices across teams.
Master’s degree in Computer Science or a related technical field.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aisqlgojavapythonjavascript

Platform: greenhouse
Effort: quick