Data Engineer

Mandatory Technical Skills:

Databricks PySpark Python SQL

Any Cloud(Azure/AWS/GCP)

Role & responsibilities

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Databricks and PySpark.
• Develop data processing and transformation workflows using Python and SQL.
• Work with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Perform data cleansing, validation, transformation, and integration across multiple data sources.
• Optimize Spark jobs, SQL queries, and data processing workflows for performance and cost efficiency.
• Implement data quality checks, error handling, and monitoring mechanisms.
• Collaborate with data architects, analysts, and other engineering teams to deliver reliable data solutions.
• Troubleshoot pipeline failures and resolve data processing and performance-related issues.
• Follow best practices for data security, governance, and development standards.

Preferred candidate profile

The ideal candidate will have 5 Years of strong hands-on expertise in Databricks, PySpark, Python, and SQL, along with cloud experience. The candidate should be capable of developing scalable, high-performance data pipelines and delivering reliable data engineering solutions in a cloud environment.