Lead Engineering Manager

Weekday AI; United States; Remote; USD 150,000 - 230,000; Full time

Job summary

Weekday AI is seeking a Lead Engineering Manager to architect and deliver real-time streaming solutions. You will mentor engineering teams, translate business needs into robust systems, and collaborate with cross-functional stakeholders to define technical roadmaps.

You will drive the design of distributed backend services, optimize high-throughput pipelines, and ensure best practices in CI/CD, testing, and observability across cloud deployments.

Qualifications

• 10–12 years of software engineering experience with distributed systems.
• Strong hands-on Apache Flink experience with windowing, state management, and event-time processing.
• Advanced Java proficiency including concurrency and performance tuning.
• Experience with cloud deployments (AWS/Azure/GCP) and containerization (Docker, Kubernetes).
• Experience with SQL and NoSQL databases and messaging systems like Kafka.
• Proven record leading engineering teams and driving technical initiatives.
• Strong problem-solving, communication, and cross-functional collaboration skills.

Responsibilities

• Lead architecture, design, and implementation of real-time data pipelines using Flink.
• Develop high-performance backend services and distributed systems in Java.
• Design scalable event-driven architectures for high-throughput, low-latency workloads.
• Optimize streaming jobs for performance, fault tolerance, and resource efficiency.
• Ensure code quality, testing, observability, and CI/CD practices.
• Collaborate with data engineering, DevOps, and product teams on roadmaps and requirements.
• Mentor engineers and promote technical excellence and continuous improvement.
• Contribute to infrastructure decisions around cloud deployment and containers.

Skills

Apache Flink

Java

Distributed systems

Kafka

Kubernetes

Docker

Cloud (AWS/Azure/GCP)

CI/CD

SQL/NoSQL

Tools

Kafka

Docker

Kubernetes

Job description

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.

Requirements

Key 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.