About the role
InsuranceDekho is hiring Data Engineers to build and maintain scalable data pipelines and ETL workflows. The role requires strong SQL and Python skills along with experience working with databases, data warehouses, and cloud platforms. Knowledge of Spark or Airflow is a plus. HOW TO APPLY: Apply through the Google Form.
Responsibilities
- Build and maintain scalable data pipelines.
- Develop and manage ETL workflows.
- Work with databases and data warehouses to support data processing requirements.
- Use SQL and Python to develop and maintain data engineering solutions.
- Work with cloud platforms for data engineering workloads.
- Ensure data pipelines are reliable, scalable, and efficient.
- Work with technologies such as Spark and Airflow where applicable.
Requirements
- Strong SQL skills.
- Strong Python programming skills.
- Experience working with databases.
- Experience with data warehouses.
- Experience with cloud platforms.
- Understanding of ETL workflows and data pipelines.
- Knowledge of Spark or Airflow is a plus.
Benefits
- Opportunity to work on scalable data engineering systems.
- Hands-on experience with data pipelines and ETL workflows.
- Exposure to databases, data warehouses, and cloud platforms.
- Opportunity to work with technologies such as Spark and Airflow.
- Learning and career growth opportunities in data engineering.
Required Skills
Frequently Asked Questions
What is the salary for Data Engineer?
The listed salary for Data Engineer at InsuranceDekho is CTC: 10–30 LPA.
Where is this Data Engineer role located?
This position is based in Gurgaon (Not specified).
How do I apply for Data Engineer at InsuranceDekho?
Apply directly through the application link on this HireDoor job page for Data Engineer at InsuranceDekho.
What are the key benefits for Data Engineer?
Key benefits include: Opportunity to work on scalable data engineering systems.; Hands-on experience with data pipelines and ETL workflows.; Exposure to databases, data warehouses, and cloud platforms.; Opportunity to work with technologies such as Spark and Airflow.; Learning and career growth opportunities in data engineering..