Manager, Software Engineering

Be hands-on with code, maintaining high technical standards and actively participating in design and architecture decisions, code reviews, and helping engineers optimize their code. Leverage deep experience in the data domain to design and build scalable data pipelines and lead business intelligence initiatives, supporting the growth and optimization of our modern data platform. Provide technical leadership and direction for major projects, ensuring alignment with business goals and industry best practices. Lead by example in AI augmented development: use AI tools for architecture exploration, code review acceleration, query optimization, and rapid prototyping of data pipelines and BI logic. Ensure that high standards of performance, scalability, and reliability are maintained when architecting, designing, and developing complex software systems and applications. Ensure accountability for the team's technical decisions and enforce engineering best practices (e.g., documentation, automation, code management, security principles, leverage CoPilot). Ensure the health and quality of services and incidents, proactively identifying and addressing issues. Utilize service health indicators and telemetry for action. Implement best practices for operational excellence. 8+ years of experience in software development, with 3+ years in a technical leadership role and 2+ years in a people management role. Experience in Data and analytics domain with hand on experience with tools like looker, cognos, PowerBI, or Tableau, ect. Proven track record of leading and delivering large-scale, complex software projects. Deep expertise in one or more programming languages such as C, C++, C#, .NET, Python, Java, or JavaScript. Demonstrated experience with AI assisted development tools (e.g., Claude Code, GitHub Copilot, or equivalent) and a proven ability to drive AI tool adoption within an engineering team. including establishing usage norms and measuring productivity impact. Extensive experience with software architecture and design patterns. Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. Strong understanding of cloud technologies and DevOps principles. Excellent communication and leadership skills, with a demonstrated ability to influence and drive change. Master's degree or PhD in Computer Science, Engineering, or a related technical field. Experience with cloud platforms like Azure, AWS, or GCP. Familiarity with CI/CD pipelines and automation tools.