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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.
Experience
1-3 yrs
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