Avra - Data Engineer
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Requirements
• Experience - 2–4 years of experience in data engineering, backend engineering, or related roles • Technical Skills - Experience with Python and SQL, and some exposure to data pipelines or distributed systems • Mindset - Strong learning orientation and willingness to take feedback and iterate quickly • Mindset - • Collaboration - Ability to work in a team, communicate clearly, and ask for help when needed • Collaboration -
Responsibilities
• Build and maintain data pipelines. Implement pipelines that ingest and process data from APIs, files, and external systems. • Build and maintain data pipelines. • Contribute to orchestration workflows. Work with tools like Dagster (or similar) to build and maintain data workflows. • Contribute to orchestration workflows. • Support data modeling efforts. Help structure datasets and transformation layers to improve usability and consistency. • Support data modeling efforts. • Work with real-world data issues. Investigate data inconsistencies, handle schema changes, and debug pipeline failures. • Work with real-world data issues. • Improve reliability over time. Add monitoring, logging, and checks to make systems more observable and stable. • Improve reliability over time. • Collaborate with the team. Work closely with senior engineers and other teams to understand problems and implement solutions. • Collaborate with the team. • You Stand Out If • You Stand Out If • You have experience working with data pipelines or backend systems • data pipelines • You are comfortable writing Python for data processing or automation • Python • You have solid SQL skills and understand basic data modeling concepts • You are curious about how systems work in production and want to understand failures • You are comfortable asking questions and digging deeper into problems • You prefer simple, clear solutions over unnecessary complexity • Experience with tools like dbt, Airflow, Dagster, or cloud platforms is a plus
Benefits
• Competitive Compensation - Attractive salary and equity participation • Ownership & Impact - Direct influence on the foundation of Avra’s data platform and its evolution • Ownership & Impact - • Technical Environment - Work on real-world data problems involving complex ingestion, reliability, and large-scale systems • Technical Environment - • Lean, High-Quality Team - Work closely with experienced engineers and founders in a high-context environment • Lean, High-Quality Team - • Flexible Culture - Remote-first (Brazil), with flexible time off and a strong focus on autonomy • Flexible Culture - • If you’re looking to grow as a data engineer by working on real systems — not just isolated tasks — and want to learn how production data platforms actually work, we’d love to hear from you.
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