data engineer for an AI-powered health coaching app

Simple Life is an AI-powered health coaching app for adults who want to lose weight and adopt healthier habits. The product provides personalized support and has helped millions of users pursue sustainable weight loss.

• Design, build, and maintain streaming pipelines;
• Develop custom ingestion pipelines from third-party APIs, webhooks, and SDKs;
• Migrate existing data ingestion pipelines from SaaS tools to internal infrastructure;
• Deliver data to the raw layer of the Snowflake warehouse with schema consistency, idempotency, and resilience to malformed or late data;
• Evolve the AWS streaming stack, including Kinesis, SQS, Lambda, and API Gateway, to improve cost efficiency, observability, and resilience;
• Maintain Terraform infrastructure as code for ingestion and processing resources;
• Monitor pipelines, troubleshoot issues, and resolve incidents;
• Contribute to safe data access for AI agents and tooling;
• Continuously improve ingestion architecture, tooling, and engineering practices.

• 5+ Years of commercial Python experience in a backend or data engineering role;
• Solid understanding of distributed systems architecture, including load balancing, sharding, and synchronous and asynchronous processing trade-offs;
• Hands-on experience with cloud services, preferably AWS, including Lambda, API Gateway, and containers in ECS/EKS;
• Experience building streaming pipelines with Kinesis, SQS, or equivalents;
• Experience with infrastructure as code using Terraform or equivalents;
• Working knowledge of SQL, including joins and window functions;
• Commercial experience with real-world production data and systems that handle messy, duplicated, delayed, or malformed input;
• Solid understanding of data flows through production systems and downstream issue prevention;
• Operational mindset and comfort owning production systems and monitoring them;
• Ability to make architectural decisions independently and review teammates’ work;
• Nice to have: strong SQL and data modeling skills, Snowflake and dbt experience, workflow orchestrators such as Airflow, Dagster, or Prefect, experience working with analytics and product teams as a data provider, experience with sensitive or regulated data.

• Competitive salary package based on expertise, skillset, and product impact;
• Stock options;
• Equipment needed for productive work;
• Premium SIMPLE subscription;
• 21 Days of annual leave plus bank holidays observed where the employee lives;
• Flexible hours focused on results;
• Open-minded teams and an inclusive company culture.