Singapore
Skilled Data Engineer offering a strong background in developing data pipelines ETL in Python, performing data migration and creating visualisation dashboard. Proficient in a range of skills that contribute to cloud data platforms, programming languages, tools and testing methodologies. Big Data Management Platforms: Azure, PostgreSQL, Spark, Hadoop, Informatica Programming Languages: Python, SQL Data Visualisation tools: Power BI, Tableau Data Integration tools: Airflow, Github Python Libraries: Pandas, Matplotlib, Seaborn, Numpy, Sqlalchemy
- Collaborated with cross-functional stakeholders to understand user requirement and build ETL pipelines for data visualization using Tableau - Develop ETL pipelines to process data from existing datawarehouse, perform data cleansing & aggregations and map into new database using MSSQL - Build Tableau Dashboards to monitor key performance of company from multiple aspects, and derive actionable insights
Enterprise Data Governance and Analysis Division - Build ETL pipeline to ingest data from Hive database, conduct data cleansing to improve data quality, and map into target repository using Informatica ETL tool - Perform rigorous data analysis for different types of finance products in hadoop ecosystem using SQL to derive actionable insights - Implement automated data validation and quality control mechanism to streamline the data analysis process, minimizing the need for manual intervention using Python
- An intensive training programme designed to equip learners with on-demand tech skills to pivot to new career opportunity in the tech industry. Project 1 Highlights: - Design and build reliable pipelines to ingest data of an e-Commerce site, and load into PostgreSQL database after data cleaning. - Creates dashboard for data visualization on Power BI, provides recommendation and improvements based on the insights. Project 2 Highlights: - Build crawler to extract data from Twitter by using Twitter API, conduct data optimization and write into PostgreSQL database using Jupyter Notebook - Performs data manipulation on the database with SQL query language to transform data into an easily analyzed format.
- Investigate, analyses, and identify root cause of low yield triggered on wafer processing and implement actions to prevent repetitive defects - Involves in experiments planning (DOE), data collection, process diagnosis and process improving solution to optimize the process flow - Apply statistical process control (SPC) and data analysis skills in process control, by monitoring out of specification conditions, and implement corrective actions
- Design and preparation of mechanical drawing with using Solid Edge and AutoCad; interact closely with Production Engineers to solve technical issues during fabrication - Performs reconfiguration and calculation on the efficiency of heat exchanger especially on Charge Air Cooler, Shell & Tube Cooler, and Plate Heat Exchanger - Review engineering drawing to ensure adherence to ASME specification and standard