1. Work closely with data scientists to understand the requirements for model training and inference.2. Prepare and preprocess data to be used as input features for machine learning models.3. Help Business to overcome the data challenges and provide suitable data analysis and technical solution to make their planning smoothly 4. Implement feature engineering processes to extract relevant information from raw data.5. Integrate and transform raw data into formats suitable for machine learning applications.6. Ensure the accuracy and reliability of data by implementing data quality checks.7. Identify and address data quality issues as they arise.8. Implement and maintain ETL (Extract, Transform, Load) pipelines.9. Manage environments to ensure consistency between development, testing, and production.10. Implement automation in data engineering tasks, including data processing and deployment, Development automated reporting solutions to streamline repetitive tasks and ensure timely delivery of insights.11. Continuously enhance skills in data analysis and visualization techniques.

1. Collect and compile data from various sources, including databases, spreadsheets, logs, and external APIs.2. Clean and preprocess data to ensure accuracy, consistency, and completeness.3. Handle missing data, outliers, and anomalies.4. Handling tools like Tableau, Power BI, visualization.5. Develop automated reporting solutions to streamline repetitive tasks and ensure timely delivery of insights.6. Apply analytical and critical thinking skills to solve business problems and identify opportunities for improvement.