About Fresha
Fresha is the AI-powered operating system for the global beauty, wellness and self-care industry, connecting and powering everything from salons and barbers to spas, medspas, fitness studios and health practices.
Trusted by millions of consumers and businesses worldwide. Fresha is used by 140,000+ businesses and 450,000+ stylists and professionals worldwide, processing over 1 billion appointments to date.
The company is headquartered in London, United Kingdom, with 15 global offices located across North America, EMEA and APAC.
Responsibilities:
- Design, develop, and maintain data pipelines using Kafka and other tools
- Build and maintain infrastructure using Terraform
- Troubleshoot and resolve data engineering issues
- Work with other teams to ensure that data is available and accessible
- Stay up-to-date on the latest data engineering trends and technologies
- Take part in decisions related to how we undertake new projects
- Gather requirements and scope out projects with the rest of the team
Qualifications:
- Bachelor's degree in Computer Science or a related field
- 5+ years of experience as a Data Engineer
- Strong understanding of Kafka, Spark, Flink, and standard computer science concepts
- Experience with cloud-based infrastructure (AWS, Azure, GCP)
- Excellent communication and problem-solving skills
- Ability to work independently and as part of a team
Nice to have haves:
- Experience with relational databases (PostgreSQL)
- Experience with Snowflake
- Experience with Flink & Spark
- Experience with "NoSQL" databases (Redis, ElasticSearch, etc.)
- Experience with high availability systems and event-driven systems.
Benefits:
- Competitive salary and benefits package
- Opportunity to work on cutting-edge technology
- Chance to make a real impact on a growing company
- Work with a team of talented and passionate engineers
Interview Process
- Informal meeting with Talent Partner (1 hour)
- 1st Stage Interview with Head of Data & Infrastructure (30 minutes)
- 2nd Stage Technical Google Hangout OR onsite with 2 members of the data Engineering team (Up to 2.5 hours)
- Final Stage Google Hangout interview with CTO (1 hour)