Responsibilities
- Design and implement data pipelines using Databricks platforms
- Develop and optimize ETL workflows for large-scale datasets
- Collaborate with analytics and data science teams to support data needs
- Ensure data accuracy, consistency, and accessibility across systems
- Build and maintain data models and warehouse structures
- Troubleshoot and resolve data integration issues
- Support the deployment of data solutions in production environments
- Participate in code reviews and technical design discussions
- Monitor data pipeline performance and reliability
- Implement data quality checks and validation processes
- Work with cloud-based data storage and processing technologies
- Document data architectures and engineering processes
- Contribute to the improvement of data engineering standards
- Assist in the migration of legacy data systems to modern platforms
- Integrate data from multiple source systems
- Apply software engineering best practices to data workflows
- Use version control systems for data pipeline code
- Collaborate on data security and compliance requirements
- Support data governance initiatives
- Engage in agile project planning and delivery cycles
- Stay current with advancements in data technologies
- Provide technical guidance to team members
- Optimize data processing efficiency and cost
- Ensure scalability of data infrastructure
- Participate in on-call rotations when necessary
Work Arrangement
On-site
Team
supportive team environment
