Databricks Engineer

Job Description

We are looking for an experienced Databricks Engineer with 5-8 years of experience in designing, developing, and optimizing large-scale data solutions. The ideal candidate should have strong expertise in Databricks, PySpark, Spark, SQL, cloud platforms (AWS/Azure/GCP), and modern data engineering practices to build scalable and high-performance data pipelines.

Roles & Responsibilities

• Roles & Responsibilities


• Design, develop, and maintain data pipelines using Databricks.


• Build ETL/ELT workflows for large-scale data processing.


• Develop and optimize data transformation logic using PySpark and Spark SQL.


• Implement and manage Delta Lake for reliable and efficient data storage.


• Work with batch and real-time data ingestion frameworks.


• Monitor and optimize data pipelines for performance and scalability.


• Collaborate with data analysts, data scientists, and business stakeholders.


• Ensure data quality, security, and governance standards are followed.


• Troubleshoot production issues and provide ongoing support.

Technical Requirement

• 5-8 years of experience in Data Engineering and Big Data technologies.


• Strong hands-on experience with Databricks, PySpark, and Spark SQL.


• Experience with Delta Lake, Databricks Workflows, and Unity Catalog.


• Proficiency in Python and SQL.


• Experience with Azure/AWS/GCP cloud platforms.


• Knowledge of Azure Data Factory (ADF), Apache Airflow, or similar orchestration tools.


• Understanding of data warehousing concepts and ETL/ELT methodologies.


• Experience with Kafka/Event Hub for streaming data processing is preferred.


• Familiarity with Git, CI/CD pipelines, and DevOps practices.


• Strong problem-solving, analytical, and communication skills.

Educational RequirementMCA,MSc,MTech,BTech

Preferred SkillsTechnology->Data Engineering->Databricks

Service LineData & Analytics Unit