Data Engineering Manager, Rad AI

• 6+ years of relevant experience in data engineering
• 2+ years of experience in management roles, preferably in the data engineering field
• Proven track record of leading and managing high-performing data engineering teams
• Expertise in designing and developing distributed data pipelines using big data technologies on large scale data sets
• Deep expertise in designing, planning, productionizing, maintaining, and documenting reliable and scalable data infrastructure and data products in complex environments
• Experience with big data processing and analytics on AWS, using services such as Amazon EMR and AWS Batch
• Experience in large scale data processing technologies such as Spark
• Expertise in orchestrating machine learning workflows using tools like Metaflow
• Experience with various database technologies, including SQL and NoSQL databases (e.g., AWS DynamoDB, ElasticSearch, PostgreSQL)

Desirable

• This role will lead our Data Engineering team to support our rapid client growth and projected expansion in the year ahead. In this role, you will play an instrumental part in the construction and maintenance of data collection systems, pipelines, and management tools, as well as managing the data engineering team
• As the authority over the construction and continued operation of Rad AI data systems
• Manage a team of data engineers at a variety of levels
• Collaborate with ML engineers and researchers to understand their data needs, including model training and production monitoring systems, and develop solutions that meet those requirements
• Provide mentorship and guidance for your team members, helping them grow in their technical responsibilities, setting direction, and ensuring timely delivery of new features
• Ensure data quality, integrity, and security by implementing robust data validation, monitoring, and access controls
• Evaluate and recommend data technologies and tools to improve the efficiency and effectiveness of the data engineering process
• Continuously monitor, maintain, and improve the performance and stability of the data infrastructure
• Determine the roadmap, direction, and priorities for the data engineering team, aligning with the company's strategic goals and objectives