Databricks Data Engineer

Overview

We are looking for a highly skilled Databricks Data Engineer with 3-9 years of experience to design, develop, and optimize scalable data solutions. The ideal candidate will have expertise in Databricks, PySpark, Python, data modeling, and ETL, with a strong understanding of DevOps practices.

Key Responsibilities:

• Design and implement data pipelines in Databricks using PySpark and Python.
• Develop and optimize ETL/ELT workflows for structured and unstructured data.
• Create scalable data models to support analytical and business needs.
• Work with Azure/AWS/GCP Databricks environments for data processing and analytics.
• Ensure data quality, governance, and performance optimization in Databricks.
• Collaborate with data scientists, analysts, and DevOps teams to streamline data operations.
• Leverage DevOps principles for CI/CD, infrastructure automation, and monitoring.
• Implement best practices for data security, performance tuning, and cost optimization.

Preferred Skills & Qualifications:

• Hands-on experience with Databricks and PySpark for Big Data processing.
• Proficiency in Python, SQL, and data modeling techniques.
• Strong knowledge of ETL/ELT pipeline development in cloud environments.
• Understanding of DevOps concepts, including CI/CD, Docker, Kubernetes, and Terraform.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and their data services.
• Excellent problem-solving skills and the ability to work in a fast-paced environment.

Job Type: Full-time

Pay: ₹850,000.00 - ₹3,000,000.00 per year

Work Location: In person