Data Engineer
Role details
Job location
Tech stack
Job description
️ Pipeline Development: Develop and maintain ETL/ELT processes using dbt and Snowflake to efficiently manage and transform large datasets
️ Documentation & Process Creation: Establish clear, efficient processes for data handling and write documentation for end-to-end pipeline management
️ Own the end-to-end process: Including the injection of new data into our production environments and supporting customer success to delight the client during this migration
Requirements
You'll make sure recruitment firms can move smoothly from their legacy systems to Spott.
️ You can navigate undocumented systems, reverse-engineer data models on the fly, and solve problems through experimentation.
️ You approach complex data challenges with practical, solutions-focused thinking.
️ Experience with dbt, SQL, PostgreSQL, Snowflake and Python
️ Experience with Terraform and Azure is a plus
Benefits & conditions
️ Competitive salary and generous stock options
️ The chance to grow with us and achieve your career aspirations.
️ Great team vibe with regular dinners, sports activities and international offsites
Overall, if joining a high growth company, with an extremely talented & ambitious team sounds appealing to you, then you should apply - even if you don't match all criteria
About the interview process
- Application Review
We'll review your application, in 48 hours you will hear back from us
- Founder call (30min)
A 30min call with Manu to learn about your motivations to join Spott, determine why you'd be a great fit, and answer any questions you may have for us
- Technical Interview (60 min)
We talk through a typical data migration problem we face at Spott to learn more about how you think as an engineer
- Founder Chat
A final chat with two of the founders to align on mission, expectations, and team fit.