• Lead the design, development, and maintenance of the data infrastructure and ETL (Extract, Transform, Load) processes to support the data needs of various departments.
• Collaborate with stakeholders to understand data requirements and implement scalable solutions for data ingestion from multiple sources.
• Ensure data quality and integrity by implementing data validation checks, data cleansing techniques, and data governance practices.
• Develop and maintain efficient data pipelines and workflows for data transformation and enrichment.
• Deploy and Develop machine learning data pipelines in coordination with Data Scientist and Data Analyst
• Design and implement data models, databases, and data warehouses to optimize data storage and retrieval.
• Work closely with software developers to integrate data engineering solutions into business applications and systems.
• Optimize data processes and infrastructure for performance, scalability, and cost-effectiveness.
• Implement and maintain data security and access controls to protect sensitive information.
• Monitor and troubleshoot data pipelines, identify and resolve data-related issues promptly.
• Stay up-to-date with emerging technologies, tools, and trends in data engineering and recommend innovative solutions to improve data infrastructure and processes.
• SQL & Python
• AWS, GCP or AZURE
• Data Visualization Tools
• Machine Learning Deployment on Cloud