About the role
We are looking for a Data Engineer with hands-on experience in Apache Airflow, Python, and Jupyter Notebook to build, orchestrate, and maintain robust data pipelines that power our analytics and business decisions.
Responsibilities:
- Design, build, and maintain scalable ETL/ELT data pipelines using Airflow and Python.
- Schedule, monitor, and troubleshoot DAGs to ensure reliable data flow.
- Perform data extraction, cleaning, transformation, and validation from multiple sources.
- Use Jupyter Notebook for exploratory data analysis, prototyping, and pipeline testing.
- Collaborate with data analysts, data scientists, and product teams to understand data requirements.
- Ensure data quality, integrity, and pipeline performance at scale.
- Maintain clear documentation of pipelines and data workflows.
Requirements:
- 1-2 years of hands-on experience in data engineering.
- Strong proficiency in Python for data processing and scripting.
- Working experience with Apache Airflow (DAG design, scheduling, orchestration).
- Comfortable working in Jupyter Notebook for analysis and prototyping.
- Good understanding of SQL, databases, and data modeling concepts.
- Familiarity with cloud platforms (AWS/GCP/Azure) is a plus.
Preferred:
- B. Tech/B. E. from NIT or IIT.
- Exposure to big data tools (Spark, Kafka) or data warehousing concepts is a plus.