Senior Data Engineer

About the role

Simple Life, the leading AI‑powered health coaching app, is seeking a Senior Data Engineer to design and operate its real‑time data ingestion platform. You will work with a global tech team to ensure reliable, scalable streaming pipelines that feed the Snowflake data warehouse.

Key responsibilities

• 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 Snowflake with schema consistency, idempotency, and resilience to malformed or late data.
• Evolve the AWS streaming stack (Kinesis, SQS, Lambda, API Gateway) for cost efficiency, observability, and resilience.
• Maintain infrastructure as code using Terraform for ingestion and processing resources.
• Monitor pipelines, troubleshoot incidents, and ensure reliable operation.
• Contribute to safe data access for AI agents and tooling.
• Continuously improve ingestion architecture, tooling, and engineering practices.

Required profile

• 5+ years of commercial Python development in a backend or data engineering role.
• Strong understanding of distributed systems architecture, including load balancing, sharding, and sync/async trade‑offs.
• Hands‑on experience with AWS services (Lambda, API Gateway, containers in ECS/EKS) and streaming technologies (Kinesis, SQS or equivalents).
• Proven ability to design production‑grade pipelines that handle messy, duplicated, delayed, or malformed data.
• Operational mindset with ownership of production systems and incident response.
• Ability to make independent architectural decisions and review teammates’ work.

Required skills

• Python
• AWS Lambda
• AWS API Gateway
• AWS ECS
• AWS EKS
• Amazon Kinesis
• Amazon SQS
• Terraform
• Snowflake
• dbt
• SQL (joins, window functions)
• Data modeling
• Airflow
• Dagster
• Prefect