- Опыт
- 2+ года
- Зарплата
- —
- Открытия
- 1
- Опубликовано
- 4 часа назад
- Режим работы
- Работа из дома
- Критерии отбора
- Candidates with 2+ years of experience in data engineering or backend engineering for data-intensive systems, and those who can work independently while collaborating across teams, are suitable. Applicants should be comfortable in a remote, asynchronous setup.
- Резюме
- Необходимо подать заявку.
Описание работы
Role overview
Redpapr is creating an AI-enabled learning platform for UPSC, NEET, and JEE learners. The role of Data Engineer sits at the center of this product, with responsibility for building the data foundation that powers personalization, analytics, and product experiences at scale.
What the role involves
- Develop dependable ETL and ELT processes that can handle both structured and unstructured data.
- Set up and support data ingestion flows using orchestration tools such as Airflow.
- Create and maintain data structures, models, and schemas across PostgreSQL, S3, and related storage systems.
- Partner with AI engineers and analysts to supply clean, clearly documented datasets for downstream use.
- Protect the quality of data by keeping it accurate, consistent, and traceable across the stack.
- Add monitoring, logging, and alerting so pipeline issues can be detected and resolved quickly.
Required background
- At least 2 years of experience working as a data engineer or as a backend engineer on data-heavy systems.
- Strong hands-on ability in Python and SQL.
- Experience using workflow orchestration or data pipeline tools such as Apache Airflow, Prefect, or similar platforms.
- Working knowledge of PostgreSQL, data lakes, and cloud object storage such as AWS S3.
- Solid understanding of normalization, data versioning, and lineage concepts.
- Comfort working independently while also collaborating with different functions across the team.
Nice-to-have experience
- Exposure to streaming or near real-time pipelines using Kafka, Kinesis, or comparable tools.
- Familiarity with preparing data for machine learning and performing feature engineering.
- Experience with dbt or data cataloging tools.
- Prior work in edtech, adaptive learning, or analytics-focused products.
Tech stack
The current environment includes PostgreSQL, Airflow, S3, Redis, Docker, Metabase, dbt where needed, Python notebooks, Hugging Face, OpenAI APIs, and PyTorch.
Perks and benefits
- Remote-first work setup with asynchronous collaboration.
- Flexible work hours along with a generous leave structure.
- Opportunity to receive early-stage equity.
- Chance to build data systems that directly influence student outcomes.
Application details
Interested candidates are asked to share a resume, a GitHub profile or portfolio if available, and a short note describing their background and interest in data engineering. The contact email provided is redpapr@gmail.com.