Responsibilities
- Own data architecture for large-scale, high-impact projects while balancing scalability, reliability, performance, maintainability, and operational cost.
- Design, build, and operate scalable data pipelines and systems for ingesting, transforming, storing, and serving large volumes of data.
- Partner with Software Engineering, Data Science, Product Management, and other stakeholders to translate data requirements into technical solutions.
- Define and own data quality, reliability, and SLA/SLO requirements for datasets and systems.
- Design and optimize data models, databases, and complex SQL workloads for query performance, storage efficiency, and scalability.
- Build reusable frameworks, tooling, and infrastructure for data product development and maintenance.
- Identify opportunities to use data to improve products, customer experiences, and business outcomes.
- Establish engineering practices for testing, observability, deployment, and operational excellence in data systems.
- Mentor engineers through technical guidance, design reviews, and actionable feedback.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
- At least 5 years of software or data engineering experience building production systems.
- Strong programming experience in one or more of Go, Java, C++, Python, or JavaScript, together 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 with relational and/or NoSQL databases and their performance and scalability characteristics.
- Ability to independently drive projects from technical design through implementation, deployment, and operation.
- Preferred experience with large-scale data platforms, data warehouses, distributed data systems, cloud data infrastructure, and high-throughput data pipelines.
- Preferred knowledge of database architecture, data modeling, query optimization, indexing, partitioning, storage systems, and complex SQL workload optimization.
- Preferred experience with Kafka, Spark, Flink, Trino/Presto, BigQuery, Snowflake, or similar distributed data technologies.
- Preferred experience with data quality, observability, monitoring, production reliability, and unit, integration, and data quality testing.
- Preferred experience providing technical mentorship and driving engineering best practices across teams.
- A Master’s degree in Computer Science or a related technical field is preferred.
Tech Stack
Categories
About DevRev
Computer is the most precise, efficient, and safe AI platform for enterprise search, employee service/help desk, and customer support (including voice). It works by unifying all your existing systems and data into a patented, AI-ready knowledge graph: Native Shared Memory. Every tool, every team, every customer conversation lives in this compounding context. So every answer and action is grounded in what your company knows, and how it operates. With permissions and safety guardrails respected, always. PROVEN EFFICIENCY, PRECISION, AND SAFETY We tested Computer against the market-leading AI on enterprise data: – 48% more accurate – 4.4x fewer tokens used – Cost stays flat at 256x data growth (vs. 29% growth) These results are from “Enterprise-Bench” – the AI industry’s first open, vendor-neutral benchmarking tool. Developed with Laude Institute, validated by Professor Alexandros Dimakis (UC Berkeley). The benchmark model, dataset, and traces are all public. (Feel free to get in touch to learn more.) REAL-WORLD RESULTS More and more companies are trusting Computer: – Bolt: 40% faster ticket resolution. 43% cut in live ticket volume. 25% increase in customer retention. – Bill: 70% of support tickets fully resolved without a human. 100% deployment across all market segments in 15 weeks. Up to $6M in annual savings. – $1.1B org*: 2,000+ new hires onboarded in one year without hiring extra IT staff. 10 weeks to full deployment across all teams. *We can’t reveal the name of our (very) happy customer just yet – but we will soon. DevRev is headquartered in Palo Alto, with eight global offices. We’re backed by Khosla Ventures and Mayfield, with $150M+ raised. Founded by Dheeraj Pandey, former co-founder and CEO of Nutanix [NASDAQ: NTNX], and board member at Adobe [NASDAQ: ADBE], alongside Manoj Agarwal, former SVP of Engineering at Nutanix.