Salary
💰 $85,000 - $135,000 per year
Tech Stack
AWSCloudDockerGraphQLJavaScriptKubernetesMySQLNode.jsPostgresPythonSQLTerraformTypeScript
About the role
- Design, build, and maintain robust data reporting pipelines using AWS Glue, Lambda, and DBT, powering insights via Amazon QuickSight and internal analytics tools.\n
- Develop scalable backend services with modern technologies such as Python, Node.js, and TypeScript, ensuring code is maintainable, testable, and performant.\n
- Own complex technical challenges from end to end, contributing across the full software lifecycle, from sprint planning and design through implementation, reviews, and demos.\n
- Use AI as a force multiplier: explore LLMs, agentic tools, and AI-integrated features to accelerate development and improve the developer and user experience.\n
- Collaborate with cross-functional partners, product managers, designers, QA engineers, and fellow developers — to deliver features that align with user needs and business goals.\n
- Promote a healthy engineering culture through thoughtful code reviews, technical mentorship, and active knowledge sharing.
Requirements
- 5+ years of backend or full-stack software development experience, ideally with a focus on data-driven applications and production-level systems.\n
- Proven experience designing and maintaining data pipelines using tools like AWS Glue, Lambda, and DBT, especially in support of analytics platforms such as Amazon QuickSight.\n
- Strong programming skills in Python, Node.js, and JavaScript/TypeScript, with a solid grasp of backend architecture and scalable service design.\n
- Proficiency in working with SQL-based databases (e.g., PostgreSQL, MySQL), and understanding of data modeling for reporting and analytics.\n
- Hands-on experience with cloud-native development in AWS, including service orchestration and integration across compute and data layers.\n
- Familiarity with CI/CD pipelines (e.g., GitHub Actions, BitbucketPipelines) and modern DevOps workflows.\n
- Sound knowledge of API design, including REST and GraphQL, and experience building or integrating backend services into dashboards or external tools.\n
- Strong problem-solving mindset, with the ability to break down and tackle complex engineering challenges with curiosity and ownership.\n
- Enthusiasm for leveraging AI tools and automation to streamline development and enhance data delivery.