Manager, Data Science Platform Engineering

Job Description

• Dave is looking for an experienced and passionate people leader to manage a team in our Data organization. The Manager, Data Science Platform Engineer, will play a critical role in leading a team to design, develop, and maintain an end-to-end machine learning platform and ML model operations. • The mission of the Data Science Platform team is to create trustworthy, reliable, and scalable machine learning systems to enable the development and deployment of ML models with quality and scale. In this role, you will work on developing and maintaining ML platform services to support applications powered by ML/AI. You will develop SDKs and APIs to empower real-time, intelligent, automated customer experiences. • This position requires a capable leader and driven self-starter who can comfortably work with senior leadership, take tasks from start to finish, and enjoys working in a dynamic, fast-paced, and challenging environment.

Qualifications

• Minimum of 2 years of experience managing engineering teams is required. • Strong interpersonal and communication skills. • Proficient in programming using Python, TypeScript, C/C++, or Java. • Experience with Docker or other container-based solutions and CI/CD. • Experience with relational databases and NoSQL, as well as knowledge of cloud-based data warehouse solutions (e.g., BigQuery, Snowflake). • Experience with system monitoring, investigating, and resolving operational issues. • Experience with Cloud solutions toolings is required; previous knowledge of GCP toolings is preferred. • Experience with workflow management/automation tools such as Apache Airflow is a plus. • Experience with distributed processing systems, such as Apache Spark and Apache Beam; streaming processing; experience building backend services is a plus. • Engineering experience in ML platforms and ML ops domain is highly preferred.

Benefits

• Lead and nurture a team of talented DSP engineers; provide thought leadership, coaching, and mentoring to team members; help them grow professionally. Foster a culture of excellence and innovation. • Cultivate and strengthen partner relationships with business owners, data professionals who build/utilize ML technologies, and engineers. Optimize productivity through effective cross-functional collaboration and communication. • Communicate with clarity and consistency to internal and external parties; influence senior leadership on strategic and technical decision-making. • Develop the ML platform and operations strategy and roadmap to resolve complex business problems. Lead the DSP team's quarterly planning/prioritization and sprint activities to achieve optimal business results through innovation and strong execution. • Know your domain and code in depth. Drive the engineering craftsmanship and operation excellence of the team. Facilitate and contribute to conversations with engineers within and outside the team to develop reliable and scalable system designs and architectures.