Senior Engineering Manager/Director - Personalization Platform

Spartan Technologies, Inc. - San Francisco, CA

  • Be responsible for the technology strategy and accountable for driving delivery. You will author the technical vision and lead the development of the roadmap for the Personalization Platform.
  • Partner with the team leader, product manager, data science and other key stakeholders to identify and deliver technical solutions that can solve common problems across the enterprise.
  • Be a thought partner in relentlessly improving our ways of working and technical excellence, to increase cross-functional collaboration, test & learn velocity, throughput, autonomy, innovation, talent development.
  • Ensure the right balance between short term value creation and long-term platform investments.
  • Bring your technical excellence and expertise in distributed system architecture to build scalable, performant, extensible, and reusable, services, APIs, and systems that enable personalized experiences throughout the organization at scale
  • Be a technical role model guiding and inspiring technical craftmanship, innovation and adoption of the latest engineering best practices
  • Build and empower an outcome oriented, collaborative, trust-based, and inclusive team of world-class machine learning, data and full-stack engineers that fosters a culture of ownership, experimentation, innovation, and technical excellence
  • Champion agile development and modern product management best practices as a mean to build the right things in the right way.

You have

  • 5+ years in a leadership/management role with experience building engineering teams. Experience in recommendations and search engines is a huge plus (e.g., personalization at scale, Elasticsearch, performance benchmarks, etc).
  • 10+ years of progressing experience in software/data engineering, ideating and architecting distributed, scalable, enterprise-class systems. Ability to dive deep into system architecture, design, performance metrics, code, test plans, project plans, deployments, and operations.
  • Proficiency in the entire machine learning lifecycle implementation and management (i.e., ML Model Development and Deployment Frameworks, Data Architecture, ELT/ETL tools & concepts, Data Integration, Data Catalog and Query, Data Wrangling, Data Quality, etc.) and experience working with Data scientists.
  • Proficiency in distributed computing, micro-services architecture, caching frameworks (eg: Redis), data structures, algorithms, operating systems, NoSQL data stores (eg: MongoDB), databases and server-side technologies with an eye towards scale (PostgreSQL or MySQL), automation, resiliency, high availability, and user experience. Experience with Java/J2EE, RESTful APIs, event driven architecture, cloud computing (Google Cloud, AWS), integration patterns and machine learning stack (e.g., Airflow/Kuberflow, Dockers, Kubernetes etc.)
  • Experience with continuous integration and continuous development solutions.
  • Familiarity with A/B experimentation and data/metric-driven product development.
  • Ability to lead through influence across different groups and levels in the organization.
  • Excellent interpersonal, communication, and collaboration skills.
  • Master’s degree in Computer Science, Information Technology, Software Engineering, Electrical Engineering, or equivalent experience.

 



Posted On: Friday, July 15, 2022



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