Build a big data pipeline to ingest data from various sources like Google Big Query, AppFlyer, APIs, Postgres, etc., and save data into Snowflake using MageAI and Airflow. Use Debezium to detect changes in databases like MySQL and Postgres, triggering MageAI and Airflow. Create high-level and detailed design documents. Set up Metabase and MageAI using Docker on an EC2 instance (Linux, Unix/bash). Establish a CI/CD workflow for cloud deployment and Bitbucket. Configure AWS environment. Manage Agile processes within the team. Communicate with Japanese customers through meetings, chats, and emails, conveying requirements to the team and relaying the team's ideas back to the customer.

Build a streaming data pipeline to ingest data from blood testing IoT device using Flink. Design and implement an ETL big data pipeline for batch processing data from the streaming pipeline. Conduct high-level and detailed design of pipeline components. Create the CI/CD workflow for deployment on cloud infrastructure and integrate with Bitbucket. Set up the AWS environment for scalable data processing. Manage the Agile process within the team to ensure efficient project delivery.

Create basic and detailed design for the website Use Flask to develop an API that calculates complex blood pressure information, including upper and lower peaks Implement features and process data sourced from Google Cloud Platform (GCP) Build an OCR model using TensorFlow to analyze raw data from PDF formats Establish the CI/CD workflow for the cloud environment and GitLab Develop Docker containers used for unit testing (Docker, Unix bash) Communicate directly with Japanese customers through meetings, emails, and chats

Create basic and detailed design. Implement features to analyze the rate of correctness of each document and all documents inputted as a whole. Implement features to enhance document quality and provide suggestions to the QA department. Create CI/CD workflow using Jenkins and GitLab. Communicate directly with the Japanese customer through meetings, emails, and chats.

Create ETL batch data pipelines for hotels to display data in Power BI. Create streaming data pipelines for hotels to display data in Power BI. Develop Docker containers to host multiple tools including Airflow, n8n, and Metabase on Unix (bash). Migrate databases from local servers to the cloud. Transition Python code to cloud environments such as Azure and AWS. Utilize Debezium to detect changes in databases like MySQL and PostgreSQL, and trigger tools like mageai and Airflow. Establish CI/CD workflows for hotel data management. Train predictive models to forecast key business metrics and customer numbers for several hotels in upcoming years. Create both basic and detailed design documentation. Engage with Japanese customers through meetings, emails, and chat for effective communication.