Weekday Ai

Lead Engineer

  • Weekday Ai

Job Description

This role is for one of the Weekday's clients

Min Experience: 10 years

Location: USA

JobType: full-time

As a Lead Engineer, 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.