Senior Data Engineer

About the role

Simple Life is seeking a Senior Data Engineer to design, build, and maintain robust streaming data pipelines that power its AI‑driven health coaching platform. You will work closely with product and analytics teams to ensure reliable, scalable ingestion of third‑party and internal data.

Key responsibilities

• Design, develop, and operate streaming pipelines using AWS Kinesis, SQS, Lambda, and API Gateway.
• Create custom ingestion pipelines from third‑party APIs, webhooks, and SDKs.
• Migrate existing SaaS‑based ingestion workflows to in‑house infrastructure.
• Deliver clean, schema‑consistent data to the raw layer of Snowflake, handling idempotency and malformed or late records.
• Improve cost efficiency, observability, and resilience of the AWS streaming stack.
• Maintain infrastructure‑as‑code with Terraform for all ingestion and processing resources.
• Monitor pipelines, troubleshoot incidents, and ensure high availability.
• Contribute to safe data access frameworks for AI agents and tooling.
• Continuously refine ingestion architecture, tooling, and engineering best practices.

Required profile

• 5+ years of commercial Python development in backend or data engineering.
• Deep understanding of distributed systems, load balancing, sharding, and sync/async trade‑offs.
• Operational mindset with ownership of production systems and incident response.
• Ability to make independent architectural decisions and review peer work.

Required skills

• Python
• AWS services: Lambda, API Gateway, ECS/EKS, Kinesis, SQS
• Terraform (or equivalent IaC)
• SQL (including joins and window functions)
• Snowflake and dbt
• Streaming pipeline orchestration (Airflow, Dagster, Prefect or equivalents)
• Data modeling and strong SQL skills
• Experience with production‑grade data handling (messy, duplicated, delayed inputs)