The Data Infrastructure team is the backbone of all data-related processes at Faire. Work from the data infra team not only enables our data scientists and machine learning engineers to develop and deploy a wide variety of algorithms and models that power Faire's online marketplaces, but also empowers a variety of teams across the company to conduct high quality analytics, reporting, experimentation and research.
We are looking for a highly technical, hands-on, and mission-driven leader to lead our Data Infrastructure team to help us scale to the next level. As a director reporting directly to the Head of Data, you will have significant purview and influence on the evolution of Faire's streaming and batch data systems. Faire will soon be known as a top destination for data science and machine learning, and you will help take us there!
What you'll be doing:
Lead a team of engineers to develop and automate large scale, high-performance data storage and processing systems, as well as our experimentation and machine learning infrastructure to help us scale for where we're going over the next several years.
Develop technical strategy and processes to manage our ever-expanding data infrastructure and ETL pipelines.
Build and nurture a highly-engaged team by hiring, coaching, and instilling a sense of ownership and impact.
Work with data and engineering leadership to set both the long-term vision and near-term roadmap for the data infra team.
Manage processes and leverage your technical expertise to continually ensure your team delivers extraordinary results.
Set standards and implement solutions for infrastructure reliability, security, and scalability as well as data quality; lead data best practices broadly across the company.
What it takes:
5+ years industry experience in data/software engineering.
3+ years experience directly managing data engineering or software engineering teams who support scalable production systems.
Experience building/maintaining ETL pipelines and leading medium/large scale data infra projects.
Familiar with modern data technologies/stack such as Airflow, Kubeflow, Redshift, Snowflake, SQL, AWS, Docker, BigQuery, Python, Git, etc.; experience with DBT a plus.
Experience in machine learning workload and AI powered products a plus.
Experience developing data science platforms such as experimentation and machine learning platforms a big plus.
Excel in undefined environments and get excited about finding solutions to complex technical challenges, and then building them.
Passionate about coaching and leading other engineers, but love to code when the opportunity arises.
Passionate to keep up with the industry trends and continuously identify new tools to use to solve technical problems.
Experience hiring for fast-growing startups a plus.