Data Engineer

TL;DR

Data Engineer: Designing and maintaining data pipelines and analytical models to ensure data reliability and scalability. Focus on building data integrations, resolving production issues, and contributing to engineering best practices.

What you will do

• Build and maintain data integrations and pipelines (ETL/ELT, APIs, webhooks, event streams, etc.).
• Design and implement reusable analytical models (using dbt, PySpark, and other modern tools).
• Work with teams across the company to identify data opportunities and help them get the most out of the Data Platform.
• Monitor and improve production data solutions, resolving issues proactively and during on-call rotations.
• Contribute to frameworks that make data processing more efficient and speed up insights.
• Contribute to engineering best practices through code reviews, design discussions, and knowledge sharing.

Requirements

• 3+ years of engineering experience, ideally with Python.
• Proven experience building and maintaining production-grade data pipelines.
• Experience with distributed data systems (like Spark or Flink) and cloud platforms (ideally AWS).
• Strong SQL and data modelling skills.
• Hands-on experience with the modern data stack (dbt, orchestration tools, etc.) and awareness of industry trends.
• Experience in at least one business domain, such as Customer, Marketing, or Finance.

Culture & Benefits

• People-first culture with an inclusive space where different perspectives fuel our best ideas.
• Flexible hours, wellness perks, and SWAG, including performance-based bonuses and paid leave days.
• Investment in helping you unlock your potential through mentorship, coaching, and internal mobility.
• Packed with purpose – Help 100,000+ small and medium-sized businesses grow and succeed while doing meaningful, customer-driven work.