Lead Data Engineer
Posted on 9/12/2023
New York, NY, USA
Experience Level
Desired Skills
Data Analysis
Data Science
Data & Analytics
  • BA/B.Sc. in industrial/information systems engineering, computer science, statistics, or equivalent
  • 5+ years of experience in data engineering or full-stack quantitative analytics/data science roles
  • 5+ years of full-time work experience using SQL and Python in an analytics context
  • Experience with data pipelines, dimensional modeling, and dependency management
  • Experience working with data SaaS and BI tooling (Fivetran, Looker, Databricks, etc.)
  • Experience developing and managing a Looker instance
  • Experience automating data integration using APIs
  • Experience transforming open-ended objectives into well-defined requirements and delivering analytics solutions for multiple teams
  • Deep knowledge of analytics technologies, concepts, and frameworks
  • Curiosity and creativity, with sound judgment and a high degree of both integrity and empathy
  • Effective written and verbal communication of data-driven solutions across all levels of the organization
  • Proven track record of mentorship, leadership, and ownership within teams and organizations
  • Collaborate with the Business Intelligence team as well as Operators, Merchants, Marketers, Department heads, etc. to define use cases, solutions, cross-functional projects, and priorities
  • Own end-to-end implementation for complex analytics solutions throughout the company, which could include reporting, simulations, custom tooling, and models
  • Maintain a holistic vision of the organization, its data, and its customers enough to recognize and even anticipate their data needs
  • Maintain and improve the reporting infrastructure (Looker) throughout the organization, maximizing its usability and adaptation throughout the organization
  • Define, build, and launch the solutions that make it all a reality
  • Gather, transform, clean, and secure data from many sophisticated, state-of-the-art sources and destinations
  • Identify how the data can and will be used once it's all built
  • Mentor and lead other members of the data engineering team
  • Respectfully and energetically express your thoughts and data philosophy to non-technical SMEs, backing up clear reasoning behind all tool & infrastructure decisions/proposals