Lead Engineering Manager

Weekday AI; United States; Vor Ort; USD 160.000 - 230.000; Vollzeit

Zusammenfassung

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

You will lead Flink-based pipelines, develop high-performance Java services, and shape scalable, low-latency architectures across cloud deployments. Strong leadership and technical excellence are essential for success.

Qualifikationen

• 10-12 years of software engineering experience with distributed systems.
• Proficient in Java with performance tuning and concurrency knowledge.
• Strong background in stream processing and real-time analytics.
• Experience deploying apps in AWS, Azure, or GCP.
• Familiarity with Docker, Kubernetes, and event-driven architectures.
• Proven leadership of engineering teams and initiatives.
• Ability to translate business needs into robust technical roadmaps.

Aufgaben

• Lead architecture, design, and implementation of real-time data pipelines with Flink.
• Develop backend services and distributed systems in Java.
• Design scalable event-driven architectures for high throughput.
• Optimize streaming jobs for performance and reliability.
• Uphold code quality, testing, observability, and CI/CD practices.
• Collaborate with data engineering, DevOps, and product teams on roadmaps.
• Conduct design reviews and drive long-term reliability improvements.
• Mentor engineers and foster technical excellence.
• Guide infrastructure decisions for distributed processing and cloud deployment.

Kenntnisse

Distributed systems

Java

Apache Flink

Data streaming

System design

Leadership

Mentoring

CI/CD

Cloud platforms

Kafka

Tools

Docker

Kubernetes

Kafka

Jobbeschreibung

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.

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.