Data Engineer

Job Description: -Design, develop and deploy data tables, views and marts in data warehouses,operational data store, data lake and data virtualization. -Perform data extraction, cleaning, transformation, and flow. Web scraping maybe also a part of the work scope in data extraction. -Design, build, launch and maintain efficient and reliable large-scale batch andreal-time data pipelines with data processing frameworks. -Integrate and collate data silos in a manner which is both scalable andcompliant. -Collaborate with Project Manager, Data Architect, Business Analysts, FrontendDevelopers, Designers and Data Analyst to build scalable data driven products. - Beresponsible for developing backend APIs & working on databases to supportthe applications. - Workin an Agile Environment that practices Continuous Integration and Delivery. - Workclosely with fellow developers through pair programming and code reviewprocess. The teamis expected to perform Data Warehousing tasks, mainly in AWS GCC, and manageAPIs Qualifications -Proficient in general data cleaning and transformation (e.g. SQL, pandas, R,etc) to ensure data accuracy and consistency. -Proficient in building ETL pipeline (e.g. SQL Server Integration Services -(SSIS), AWS Database Migration Services (DMS), Python, AWS Lambda, ECSContainer task, Eventbridge, AWS Glue, Spring). -Proficient in database design and various databases (e.g. SQL, PostgreSQL, AWSS3, Athena, MongoDB, postgres/gis, MySQL, SQLite, voltdb, Cassandra, etc). -Experience in cloud technologies such as GPC, GCC (i.e. AWS, Azure, GoogleCloud). -Experience and passion for data engineering in a big data environment usingCloud platforms such as GPC, GCC (i.e. AWS, Azure, Google Cloud). -Experience with building production-grade data pipelines, ETL/ELT dataintegration. -Knowledge about system design, data structure and algorithms. -Familiar with data modelling, data access, and data storage infrastructure likeData Mart, Data Lake, Data Virtualisation and Data Warehouse for efficientstorage and retrieval. -Familiar with rest api and web requests/protocols in general. -Familiar with big data frameworks and tools (eg. Hadoop, Spark, Kafka, RabbitMQ). -Familiar with W3C Document Object Model and customized web scraping (e.g.BeautifulSoup, CasperJS, PhantomJS, Selenium, Nodejs, etc). -Familiar with data governance policies, access control and security bestpractices. -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