Data Engineer

Proficient in general data cleaning and transformation (e.g. SQL, pandas, R, etc) to ensure data accuracy and consistency. Proficient in building ETL pipeline (eg. SQL Server Integration Services (SSIS), AWS Database Migration Services (DMS), Python, AWS Lambda, ECS Container task, Event bridge, AWS Glue ,Spring). Proficient in database design and various databases (e.g. SQL, PostgreSQL, AWS S3, Athena, mongo db, postgres/gis, mysql, sqlite, volt db, cassandra, etc). Experience in cloud technologies such as GPC, GCC (i.e. AWS, Azure, Google Cloud). Experience and passion for data engineering in a big data environment using Cloud platforms such as GPC, GCC(i.e. AWS, Azure, Google Cloud). Experience with building production-grade data pipelines, ETL/ELT data integration. Knowledge about system design, data structure and algorithms. Familiar with data modelling, data access, and data storage infrastructure like Data Mart, Data Lake, Data Virtualisation and Data Warehouse for efficient storage and retrieval. Familiar with rest api and web requests/protocols in general. Familiar with big data frame works and tools (eg. Hadoop, Spark, Kafka, RabbitMQ). Familiar with W3C Document Object Model and customized web scraping (e.g. Beautiful Soup, CasperJS, PhantomJS, Selenium, Nodejs, etc). Familiar with data governance policies, access control and security best practices. Comfortable in at least one scripting language (eg. SQL, Python). Comfortable in both windows and linux development environments. Interest in being the bridge between engineering and analytics.