About this role.
Teachable is seeking a senior Data Engineer to serve as a technical reference for scalable data architecture, modeling standards, and production data pipelines. The role partners with Engineering, Product, Finance, and business stakeholders to convert strategic requirements into reliable data-platform solutions. Core work includes AWS-based data infrastructure, orchestration, ETL/ELT, batch and streaming systems, infrastructure as code, and management of technical debt. This is a fully remote Brazil-based employee role working on Brasília Standard Time with distributed U.S. and Brazilian teams. Success requires strong architectural judgment, hands-on delivery, and clear communication across technical and nontechnical audiences.
Role DNA
A quick view of the complexity, pace, ownership and collaboration implied by the job description.
Job Complexity
5/5Pace & Pressure
4/5Autonomy Level
5/5Communication Load
5/5Salary analysis
Estimated compensation compared with the broader US market for similar roles.
Core skills
Skills and capabilities most closely associated with this opportunity.
Sample interview questions
I would begin with data domains, source characteristics, latency needs, governance requirements, and expected growth. A typical design would separate durable storage, compute, orchestration, cataloging, and serving layers; use object storage and table formats for the lakehouse; and use managed streaming or Kafka-compatible services where low latency is justified. I would define observability, access controls, data-quality checks, lineage, cost controls, and clear ownership from the outset.
I assess the business value of freshness against the operational cost and complexity of streaming. Batch is usually preferable for scheduled reporting, backfills, and use cases where hours of latency are acceptable, while streaming fits event-driven experiences, operational alerts, or metrics requiring low latency. I also evaluate source reliability, ordering and duplication needs, downstream consumption patterns, and the team’s ability to operate the solution.
I make debt visible by documenting its operational, reliability, security, and delivery impact, then prioritize it alongside product work. I reserve capacity for foundational improvements, address high-risk debt during relevant feature changes, and use standards, reusable components, and automated testing to avoid recreating it. Stakeholders should understand the trade-off in terms of delivery speed, data trust, and long-term cost.
I would implement automated tests for schema, freshness, volume, and business-rule expectations; robust retries and idempotency; alerting tied to service-level objectives; and runbooks for common failures. I would also use version-controlled infrastructure and transformations, role-based access controls, lineage and metadata tooling, and clear ownership for each critical dataset. These practices make failures easier to detect, investigate, and correct.
I start with the decision’s business objective, such as faster reporting, lower risk, or better customer insight, rather than implementation details. I present a small set of options with trade-offs in cost, timing, reliability, and capability, then recommend the option that best fits the stated priorities. After alignment, I document assumptions, milestones, risks, and measurable outcomes so stakeholders can follow progress without needing deep technical context.
What is Teachable?
Teachable is the platform for experts and businesses who take education seriously. In a world where anyone can ask AI for information, we’re the home for those who educate with purpose, modernity, and humanity. We help experts and businesses scale their impact and operations through courses, coaching, and digital downloads that students actually love. From a finance expert teaching Python for investment analysis to a multilingual coach offering business Spanish for executives, Teachable powers human-led learning that drives student trust, connection, and results. With a sleek, intuitive interface and AI as a time-saving partner, the platform enables transformative education rooted in real-world experience. Teachable experts have lived it—that’s why they teach it.Are you ready to join a dynamic, cross-cultural team at an exciting turning point in our company’s journey?
Part of the global Hotmart Company portfolio, whose platforms have helped creators, experts, and businesses earn more than $10 billion, Teachable continues to cement itself as a true industry leader. Together, Teachable and Hotmart are delivering market-leading products that prioritize student outcomes, business growth, and flexibility. If you have big ideas, relish the chance to challenge convention, and deeply believe in the power of real-world learning to shape the future, we want you on our team!
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.
What You’ll Bring:
- 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.
Nice to Have:
- 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.
Additional Details:
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.
While Teachable maintains our NY office for local employees to use, we operate as a remote-first culture in order to give our employees added flexibility. In order to maintain connection and create a community beyond the screen, Teachable holds in-person events throughout the year, where employees and teams can come together for bonding, strategic alignment, goal-setting, and celebrations!
Teachable encourages individuals from a broad diversity of backgrounds to apply for positions. We are an equal opportunity employer, meaning we’re committed to a fair and consistent interview process. Please tell us in your application if you require an accommodation to apply for a job or to perform your job.
Annual salary information is not provided for this position. Explore salary ranges for similar roles in our Salary Directory ›
Upload your resume now
- To unlock remote work opportunities and be discovered by global employers.
This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.
