Data Engineer ( Databricks)

About the Role

We are looking for an experienced Data Engineer with strong expertise in Databricks to design, develop, and maintain scalable data pipelines and data processing solutions.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Databricks.
• Develop data processing solutions using PySpark and Python.
• Work with Apache Spark for large-scale data processing.
• Build and optimize ETL/ELT pipelines.
• Work with Delta Lake for data storage and processing.
• Develop and manage workflows using Databricks Workflows.
• Perform data transformation, cleansing, and validation.
• Optimize Spark jobs and improve pipeline performance.
• Collaborate with data engineers, analysts, and other technical teams.
• Troubleshoot data pipeline issues and ensure data quality.

Required Skills

• 3–5 years of experience in Data Engineering.
• Strong hands-on experience with Databricks.
• Good knowledge of PySpark and Python.
• Strong understanding of Apache Spark.
• Experience with Delta Lake and data lake architecture.
• Good knowledge of SQL.
• Experience in building ETL/ELT data pipelines.
• Understanding of cloud platforms such as Azure, AWS, or GCP.
• Experience with Git and CI/CD is an added advantage.

Good to Have

• Experience with Azure Databricks.
• Knowledge of Azure Data Factory, ADLS, or similar cloud data services.
• Experience with DBT, Snowflake, or other modern data platforms.
• Databricks certification is a plus.

What We Offer

• Opportunity to work on real-world Data Engineering and AI projects.
• Exposure to modern data technologies and cloud platforms.
• Collaborative and learning-focused work environment.
• Opportunity to work with a growing technology team.