Lead Engineering Manager

Weekday AI (YC W21); United States; On-site; USD 120,000 - 160,000; Full time

Job summary

A technology consulting firm in the United States is seeking an experienced Lead Engineering Manager to architect and deliver complex stream-processing solutions. The ideal candidate will have over 10 years of experience in software engineering with a strong background in Apache Flink and Java. Responsibilities include mentoring teams, collaborating with stakeholders, and ensuring high-quality technical solutions. This full-time position offers opportunities for leadership in a dynamic environment.

Qualifications

• 10-12 years of software engineering experience with a focus on distributed systems.
• Strong hands-on experience with Apache Flink and stream processing.
• Experience managing applications in cloud environments.

Responsibilities

• Lead architecture and implementation of real-time data processing pipelines.
• Develop high-performance backend services using Java.
• Collaborate with cross-functional teams to define technical roadmaps.

Skills

Apache Flink expertise

Advanced Java proficiency

Team leadership

Cloud environments (AWS, Azure, GCP)

Containerization (Docker, Kubernetes)

Job description

Overview

This role is for one of the Weekday's clients. Min Experience: 10 years. Location: USA. JobType: full-time. As a Lead Engineering Manager, you will play a pivotal role in architecting and delivering complex stream-processing solutions, mentoring engineering teams, and collaborating closely with cross-functional stakeholders to translate business requirements into robust technical systems.

Responsibilities

• Lead the architecture, design, and implementation of real-time data processing pipelines using Apache Flink.
• Develop and maintain high-performance backend services and distributed systems using Java.
• Design scalable event-driven architectures capable of handling high-throughput and low-latency workloads.
• Optimize streaming jobs for performance, fault tolerance, and resource efficiency.
• Ensure best practices in code quality, testing, observability, and CI/CD processes.
• Collaborate with data engineering, DevOps, and product teams to define technical roadmaps and system requirements.
• Conduct design reviews, troubleshoot production issues, and implement long-term reliability improvements.
• Mentor and guide engineers, fostering a culture of technical excellence and continuous improvement.
• Contribute to infrastructure decisions related to distributed processing, cloud deployment, and containerized environments.

Required Skills & Qualifications

• 10-12 years of overall experience in software engineering, with significant exposure to distributed systems.
• Strong hands-on expertise in Apache Flink, including stream processing concepts such as windowing, state management, checkpoints, and event-time processing.
• Advanced proficiency in Java, including concurrency, multithreading, memory management, and performance tuning.
• Deep understanding of data streaming architectures and real-time processing frameworks.
• Experience working with messaging systems (e.g., Kafka or similar platforms).
• Strong knowledge of data structures, algorithms, and system design principles.
• Experience deploying and managing applications in cloud environments (AWS, Azure, or GCP).
• Familiarity with containerization technologies such as Docker and orchestration tools like Kubernetes.
• Solid understanding of CI/CD pipelines, automated testing frameworks, and monitoring tools.
• Experience with SQL and NoSQL databases in high-scale environments.

Leadership & Soft Skills

• Proven experience leading engineering teams or owning major technical initiatives.
• Strong architectural decision-making abilities with a focus on scalability and maintainability.
• Excellent problem-solving and analytical skills.
• Ability to communicate complex technical concepts to both technical and non-technical stakeholders.
• Strong ownership mindset and commitment to delivering high-quality solutions.

Preferred Qualifications

• Experience with big data ecosystems and real-time analytics platforms.
• Exposure to performance benchmarking and capacity planning.
• Experience working in Agile/Scrum environments