Engineering Manager, Nexla

• 5+ years of engineering management experience leading senior engineering teams in distributed systems or data infrastructure
• 2+ years managing Senior/Principal Engineers and technical leads in high-growth technology companies
• Proven track record of building and scaling high-performing engineering teams (10+ engineers)
• Experience establishing engineering processes, best practices, and development methodologies that drive velocity and quality
• 5+ years of hands-on engineering experience in distributed systems, stream processing, or large-scale data infrastructure
• Deep expertise with Apache Kafka ecosystem including Kafka Streams, Connect, and distributed event streaming architectures
• Experience with Ray or similar distributed computing frameworks (Spark, Flink, Dask) for AI/ML data processing workloads
• Strong background in building and operating mission-critical production systems at enterprise scale
• Expert-level understanding of distributed systems concepts: consensus algorithms, fault tolerance, partitioning, replication, and consistency models
• Extensive experience with cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes, Docker)
• Deep knowledge of DevOps practices including Infrastructure as Code, CI/CD pipelines, monitoring, and observability tools
• Experience with database technologies, data warehouses, and real-time analytics systems
• Proven experience building systems that process terabytes of data daily with sub-second latency requirements
• Understanding of data serialization formats, compression techniques, and optimization strategies for high-throughput data pipelines
• Experience with stream processing patterns, event-driven architectures, and real-time data transformation systems
• Knowledge of data governance, security, and compliance requirements for enterprise data platforms

Desirable

• As Engineering Manager for the Runtime Team at Nexla, you will lead the engineering organization responsible for the core execution engines that power our data integration platform
• You'll manage a team of Engineers working on distributed systems that process massive data volumes in real-time using technologies like Kafka, our proprietary execution engine, Ray for AI data processing, and other cutting-edge distributed computing frameworks
• This role requires technical depth combined with strong leadership skills to guide high-performing engineers while establishing processes that enable teams to operate at maximum velocity
• Partner with Senior/Principal Engineers to architect scalable, fault-tolerant distributed systems capable of handling enterprise-scale data workloads
• Drive technical decisions around stream processing architectures, distributed computing frameworks, and real-time data pipeline optimization
• Establish technical standards and best practices for building mission-critical, highly available distributed systems
• Manage and mentor a team of Senior and Principal Engineers, providing technical guidance while fostering professional growth and career development
• Lead hiring efforts to attract top-tier distributed systems talent and build a world-class runtime engineering team
• Conduct performance reviews, set engineering goals, and create development plans that align individual growth with business objectives
• Foster a culture of technical excellence, innovation, and collaborative problem-solving within the team
• Design and implement engineering processes that enable high-velocity development without compromising system reliability or code quality
• Establish DevOps practices, CI/CD pipelines, and deployment strategies for distributed systems operating at scale
• Implement monitoring, alerting, and observability frameworks to ensure system health and rapid incident response
• Drive adoption of agile methodologies, sprint planning, and technical project management practices optimized for distributed systems development
• Collaborate closely with Product, and AI teams to align runtime capabilities with business requirements and customer needs
• Partner with DevOps teams to ensure seamless deployment, scaling, and operational excellence of runtime systems
• Work with the Solution and Customer Engineering teams to optimize data processing workflows and integrate new AI capabilities
• Communicate technical roadmaps, system capabilities, and engineering priorities to executive leadership and stakeholders
• Oversee the operational excellence of production runtime systems, ensuring 99.9%+ uptime
• Lead capacity planning, performance optimization, and cost management initiatives for large-scale data processing infrastructure
• Drive incident response, post-mortem analysis, and continuous improvement processes to enhance system reliability
• Ensure comprehensive disaster recovery, data consistency, and security practices across all runtime systems
• Manage 8-12 Senior and Principal Engineers with deep expertise in distributed systems
• Collaborate with specialists in AI/ML, DevOps, Platform Engineering, and Data Engineering
• Lead engineering for the core runtime systems that power enterprise data operations for Fortune 500 companies
• Build next-generation distributed systems that democratize access to real-time data processing and AI capabilities
• Work on cutting-edge problems in stream processing, distributed computing, and AI-powered data transformation
• Opportunity to build and scale a world-class engineering organization in a high-growth environment
• Direct impact on technical strategy and product direction at a fast-growing data infrastructure company
• Mentorship from experienced technology leaders and exposure to executive-level strategic decision making