Staff Software Engineer - Connectors Framework

Nexla is the leading Integration platform, built with AI, for AI. Nexla takes a metadata driven approach to converge diverse integrations across Data, Documents, Agents, Applications, and  APIs into a single design pattern. We accelerate the development of solutions for GenAI, Analytics, and Inter-company data. Nexla makes data users and developers up to 10x more productive by delivering a true blend of no-code, low-code, and pro-code interfaces.

Leading companies including DoorDash, LinkedIn, Johnson & Johnson, and LiveRamp trust Nexla for mission-critical data. Named in the 2022, 2023, and 2024 Gartner Magic Quadrant™ for Data Integration Tools and top-rated by customers on Gartner Peer Insights, Nexla is a remote-first company headquartered in San Mateo, California.

At Nexla, our culture is built around our core values: Have Empathy, Be Curious, Be Intellectually Honest, Achieve Excellence, and Remember to Relax. We put our customers at the heart of everything we do, foster a data-driven mindset, take ownership of our work, and believe in the power of teamwork to achieve ambitious goals.

• →Design and implement core connector framework features—schema evolution, intelligent pagination, rate limiting, circuit breaking—and ship them yourself.
• →Own the full lifecycle of the Connector SDK: build it, document it, dogfood it, iterate on it based on feedback from internal teams and partners.
• →Debug the hard stuff. Trace failures across Kafka clusters, distributed runtimes, and flaky third-party APIs. Fix them, then build the guardrails so they don't recur.
• →Handle "dirty" real-world data. Build self-recovery mechanisms, automated retries, and intelligent error handling that keeps pipelines running without human intervention.

• Define the technical direction for the connector framework. Solving the N+1 integration problem makes adding the 1,000th connector as easy as the 10th.
• Design for multi-tenancy, high concurrency, and low latency from day one. Our platform processes billions of rows; your architecture decisions have immediate, measurable impact.
• Evaluate and drive technology choices where to use Java/Kafka, where Rust or alternative runtimes make more sense, and how to reduce infrastructure costs without sacrificing reliability.

• Raise the bar through code reviews, design sessions, and pairing. We're a small team; your standards become the team's standards.
• Work directly with Product and the CTO to translate customer needs and market shifts (GenAI data ingestion, real-time CDC, agentic workflows) into technical plans.
• Document what you build. We don't separate building from knowledge sharing RFCs, runbooks, and SDK docs are part of the job, not an afterthought.

• 8-15+ years of software engineering, with significant time spent building platforms, frameworks, or SDKs—not just end-user applications.
• Expert-level Java/Kotlin/Scala. You understand JVM memory management, concurrency models, and non-blocking I/O at a level where you can diagnose a thread starvation issue from a heap dump.
• Deep experience with distributed systems in production: Kafka, Spark, Flink, or similar. You've operated these systems, not just used them. Bonus points for building something of your own.
• Comfort with the Modern Data Stack: Snowflake, Databricks, and the alphabet soup of protocols (gRPC, GraphQL, Webhooks, CDC).
• Startup mindset. You thrive in ambiguity. You're comfortable defining scope on the fly and shipping before the full picture is clear.
• You've owned production systems and learned the hard way what good operational discipline looks like.
• Global Collaboration Window: Ability to overlap with morning PST (Pacific Standard Time) working hours for syncs, design reviews, and collaboration with our US-based leadership and engineering teams.

• Contributions to open-source data projects (Airbyte, Flink, Debezium, Arrow).
• Experience at an iPaaS or ELT company (MuleSoft, Fivetran, Informatica, Airbyte).
• Deep Kubernetes / cloud-native experience. We run on K8s and are migrating to Strimzi for Kafka.
• Security architecture chops: OAuth 2.0, mTLS, encrypted credential management at scale.

• Impact at scale from day one. Your code processes billions of rows for companies like DoorDash and LinkedIn.
• The AI wave is real for us. We're not bolting AI onto a legacy product. Intelligent connectors, context-aware data movement, and agentic workflows are the core of what we're building next.
• Small team, big problems. You'll have direct access to the CTO, real influence over product direction, and the autonomy to make significant technical bets.
• Recognized platform with startup energy. The credibility of enterprise validation with the speed and ownership of an early-stage company.

Location - Bengaluru
Workplace type - Hybrid