Data Engineer

Since 2011, Morning has helped freelancers and small businesses manage their finances: invoices, payments, expenses and accounting. Today, 170,000 business owners use our platform. Every interaction generates data. So far, that's added up to more than 20 billion events. Our data platform turns this data into the foundation that our product, customer experience, finance, and AI teams rely on. As a Data Engineer, you'll build and run the pipelines behind it, while helping shape our next-generation company brain: a unified place where people and AI agents can access Morning's knowledge and get reliable answers. We're a small team, which means your work reaches production early and has an impact across the company, with guidance and code reviews from senior engineers along the way. What you'll do Build and maintain batch and streaming pipelines on Databricks. Transform and model data from our services into clean, reliable and accessible tables. Build data quality checks and monitoring to ensure the reliability of our data. Deploy and maintain production pipelines through CI/CD. Document data models and tables to make data discoverable and easy to use across the company. Identify opportunities to improve pipeline performance, reliability and cost efficiency. Our stack: Python, SQL, Spark, Databricks, AWS, Terraform, TeamCity. We use Claude in day-to-day development. Requirements: 4+ years of experience building production data pipelines. Strong Python and SQL. Experience with Spark. Experience with serverless architecture. Experience with Git and CI/CD. Daily use of AI coding assistants such as Claude, with the judgment to validate their output. Interest in how the data is used, not just produced. Advantages: Databricks experience. AWS experience. Terraform or other infrastructure as code. Proficiency with SQL and NoSQL databases and CDC. TypeScript and Node.js. Experience building and managing AI agents. Experience with Amazon Bedrock AgentCore.