Solution Design & Architecture: Design and architect robust and scalable data integration solutions, considering data volume, velocity, variety, and business requirements.
ETL Development: Develop and maintain ETL (Extract, Transform, Load) processes using industry-standard tools and technologies.
Data Modeling: Contribute to the design and maintenance of data models that support business needs and ensure data integrity.
Data Quality Management: Implement data quality checks and validation rules to ensure data accuracy and consistency. Develop and maintain data quality monitoring processes.
Data Governance: Adhere to data governance policies and procedures. Contribute to the development and implementation of data governance frameworks.
Performance Optimization: Identify and address performance bottlenecks in data integration processes. Optimize ETL jobs and data pipelines for optimal performance.
Integration with Various Systems: Integrate data from diverse sources, including databases, APIs, cloud platforms, and legacy systems.
Testing & Deployment: Participate in all phases of the software development lifecycle, including unit testing, deployment, and post-implementation support.
Troubleshooting & Support: Provide ongoing maintenance and support for data integration solutions, including troubleshooting issues and resolving data-related problems.
Collaboration: Work closely with business analysts, data scientists, and other stakeholders to understand data requirements and translate them into technical solutions.
Documentation: Create and maintain technical documentation for data integration processes and solutions.
