Lead Engineering Manager
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 5h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 194d ago
The date the source published, not the day we noticed it (2026-03-05). Last seen at its source 3h ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
United States
The description agrees: it names United States.
What the ad says
…Location: USA…
Pay not stated
Similar roles pay $191.9k–240k/yr
Middle 50% of 132 listings that do state pay — Engineering · Manager · United States · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
workable employer's own board first seen 10d ago · last seen 3h ago
The listing
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.