Databricks Engineer

Steady Rabbit; India; Remote; INR 1,500,000 - 2,100,000; Full time

Job summary

Steady Rabbit is seeking an experienced Data Engineer with strong Databricks expertise to design, build, and optimize scalable data pipelines. You will work with PySpark, Spark SQL, and Python to process data, develop ETL/ELT workflows, and integrate with Azure or AWS based data platforms.

The role requires hands-on Databricks experience, solid SQL and data warehousing knowledge, and strong collaboration with data analysts and engineering teams.

Qualifications

• 4+ years of experience in Data Engineering.
• Strong hands-on experience with Databricks.
• Good knowledge of PySpark, Spark SQL, and Python.
• Experience in developing ETL/ELT pipelines.
• Good understanding of SQL and data warehousing concepts.
• Experience with cloud platforms such as Azure or AWS.
• Good communication and problem-solving skills.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Databricks.
• Work with PySpark, Spark SQL, and Python for data processing.
• Develop and optimize ETL/ELT pipelines.
• Work with Azure/AWS cloud services and data platforms.
• Perform data transformation, integration, and performance optimization.
• Collaborate with data analysts, engineers, and other stakeholders.

Skills

Data engineering

Communication

Problem solving

Tools

Databricks

PySpark

Spark SQL

Python

SQL

Azure

AWS

Job description

Job Description:

We are looking for an experienced Data Engineer with strong Databricks expertise to join our team.

Key Responsibilities:

• Design, develop, and maintain scalable data pipelines using Databricks.
• Work with PySpark, Spark SQL, and Python for data processing.
• Develop and optimize ETL/ELT pipelines.
• Work with Azure/AWS cloud services and data platforms.
• Perform data transformation, integration, and performance optimization.
• Collaborate with data analysts, engineers, and other stakeholders.

Required Skills:

• 4+ years of experience in Data Engineering.
• Strong hands-on experience with Databricks.
• Good knowledge of PySpark, Spark SQL, and Python.
• Experience in developing ETL/ELT pipelines.
• Good understanding of SQL and data warehousing concepts.
• Experience with cloud platforms such as Azure or AWS.
• Good communication and problem-solving skills.