Key skills
AWSAzureCloudETLGoogle Cloud PlatformPythonSQLELTData EngineeringData WarehousingAnalyticsDatabricksGCPGoogle CloudGitVersion Control
About this role
Role Overview
- Design, develop, and maintain data pipelines using Databricks and related technologies
- Build and optimize ETL/ELT processes for large-scale data processing
- Work with structured and unstructured data across multiple data sources
- Develop and manage data models to support analytics and reporting requirements
- Collaborate with stakeholders including data analysts, developers, and business teams to understand data needs
- Ensure data quality, integrity, and governance across data platforms
- Monitor and troubleshoot data workflows and performance issues
- Contribute to continuous improvement of data engineering practices and standards
Requirements
- Minimum 2+ years of experience in data engineering
- Hands-on experience with Databricks
- Strong proficiency in Python and/or SQL
- Experience with data pipeline development and data transformation frameworks
- Familiarity with cloud platforms (e.g., Azure, AWS, or GCP)
- Understanding of data warehousing concepts and modern data architectures
- Experience with version control tools (e.g., Git)
- Strong problem-solving skills and attention to detail.
Tech Stack
- AWS
- Azure
- Cloud
- ETL
- Google Cloud Platform
- Python
- SQL