About this role
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.
What you’ll need: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
Ability to work in an office environment a minimum of 3 days a week
Enthusiasm about learning and adapting to the exciting world of AI – a commitment to exploring this field is a fundamental part of our culture