Teachable is a platform for creators who want to build a more impactful business through courses, coaching, downloadable content, and community. With Teachable, creators can engage their online audiences and get paid-on their own terms. Today, tens of thousands of creators use Teachable to share their knowledge and, to date, have reached more than 46 million students around the world.
Are you ready to join a dynamic, cross-cultural team at an exciting turning point in our company’s journey? Now part of the global Hotmart Company portfolio, Teachable continues to take the creator economy by storm as a true industry leader. Together, Teachable and Hotmart are delivering market-leading products that prioritize creator control and flexibility, alongside meaningful partnership and support from our team. If you have big ideas, relish the chance to challenge convention, and deeply believe in the power of creators to shape the future, we want you on our team!
About Your Team:
At Teachable, our Data team aims to support company data-driven decision-making. Reporting to the Head of Data, you will act as a Data Engineering technical reference, owning key architectural and platform decisions and partnering closely with Engineering, Product, and Business teams to translate strategic priorities into reliable, scalable, and high-impact data solutions.
About You:
You have a background experience with modern data architectures and engineering tools, are comfortable in supporting the design and optimization of data pipelines, modeling databases, and are constantly seeking ways to enhance data reliability, scalability, and the value delivered to stakeholders.
This is a fully remote role based in Brazil, and you’ll collaborate closely with teams across the U.S. and Brazil.
Your work will follow Brasilia Standard Time, and you’ll be hired as a CLT contract employee with compensation in BRL.
What You’ll Do:- Act as a senior technical reference in Data Engineering, setting data modeling and architectural standards and best practices for data pipelines at scale.
- Run high-impact data engineering initiatives across multiple domains, partnering with Product, Finance, Engineering and other business teams to translate strategic needs into robust data solutions.
- Balance build vs. buy decisions to maximize impact and efficiency in product analytics and infrastructure.
- Manage technical debt while ensuring scalability, reliability and maintainability.
- Proven experience as a senior data engineer, with hands-on ownership of large-scale data pipelines and complex data architectures.
- Strong technical judgment and problem-solving skills, attention to detail, and a drive to make processes more efficient.
- Strong understanding of modern data engineering best practices including data lakes, lakehouse architectures, and ETL/ELT approaches.
- Experience designing and operating cloud-native data platforms on AWS (e.g., orchestration, storage, compute, IAM), with the ability to adapt across services.
- Strong experience with orchestration and workflow tools (e.g., Airflow).
- Working knowledge of infrastructure-as-code principles and tools (e.g., Terraform) to enable repeatable, auditable environments.
- Experience building and operating batch and streaming data systems, and making informed trade-offs between them (e.g., Kafka, Kinesis, Spark Streaming).
- Strong communication skills and the ability to collaborate effectively with technical and non-technical stakeholders in a distributed, international environment.
- Data platform tooling: DBT, metadata/catalog tools.
- Eventing & integration: DMS, AppFlow, SQS/SNS.
- Architectural patterns: Data Mesh, domain-driven data.
- Engineering rigor: Experience delivering production-grade software systems.
At Teachable, we are committed to providing fair and competitive pay (using market data to inform our pay bands), rewarding high performance, and ensuring all employees have the opportunity and ability to impact Teachable’s overall company value. Base salaries will be reviewed at regular intervals throughout the year, typically following performance review cycles currently conducted annually or in conjunction with a promotion.
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