Senior Backend Engineer, Data Infrastructure

What You’re Applying For

As part of the Data Infrastructure team, you’ll help build Lemonade’s data platform for our growing stack of products, customers, and microservices.

Our platform ingests and processes data from operational databases, telematics, and diverse product sources. You’ll build robust backend services and data processing pipelines, leveraging state-of-the-art frameworks and cloud-native solutions, all while collaborating with Data Engineers, ML Engineers, Analysts, and Product Managers to turn real-world needs into resilient systems.

In this role you’ll

• Design & Develop Backend Services: Lead the design and implementation of backend systems and APIs for our distributed data platform
• Build Data Ingestion & Processing: Architect and develop scalable ingestion pipelines with streaming ETL, Change Data Capture, and large-scale batch and stream processing
• Own Data Platform Infrastructure: Implement and optimize scheduling, workflow orchestration, and data governance tools to support high-quality, compliant data flows
• Drive Engineering Standards: Establish and promote backend best practices, ensuring high reliability, code quality, and maintainability across the team
• Cross-functional Collaboration: Work closely with data engineers, ML engineers, product managers, and analysts to translate business needs into scalable backend systems
• Mentorship: Share your backend and infrastructure expertise by collaborating, reviewing, and mentoring fellow engineers.
  
  

• 5+ years of experience as a Backend, Data, or Infrastructure Engineer building large-scale backend systems and data-driven platforms.
• B.S. in Computer Science or a similar field
• Proven backend development skills with expertise in Python. Additional languages, a plus.
• Proven experience with distributed systems, microservices, building and maintaining robust backend APIs
• Proficiency with databases (SQL, NoSQL), data modeling, and streaming data architectures.
• Ability to work in an office environment a minimum of 3 days a week
• Enthusiastic about learning and adapting to the rapidly evolving world of AI and data-driven engineering
• Past experience with modern data stacks (e.g., Snowflake, Kafka, Airflow, DBT, Spark), an advantage
• Strong understanding of cloud infrastructure and orchestration (preferably AWS, K8s, Terraform/Pulumi), an advantage