Data Engineer

Responsibilities:-       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 may be also apart of the work scope in data extraction.-       Design, build, launch and maintain efficient and reliable large-scale batch and real-time data pipelines with data processing frameworks.-       Integrate and collate data silos in a manner which is both scalable and compliant.-       Collaborate with Project Manager, Data Architect, Business Analysts, Frontend Developers, Designers and Data Analyst to build scalable datadriven products.-       Be responsible for developing backend APIs & working on databases to support the applications.-       Work in an Agile Environment that practices Continuous Integration and Delivery.-       Work closely with fellow developers through pair programming and code review process.  The team is expected to perform Data Warehousing tasks, mainly in AWS GCC, and manage APIsRequirements:-       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, Eventbridge, AWS Glue, Spring).-       Proficient in database design and various databases (e.g. SQL, PostgreSQL, AWS S3, Athena, mongodb, postgres/gis, mysql, sqlite, voltdb, 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 DataMart, 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 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 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..Interested candidates may send their CV to MAC (Reg No. R1221300) [email protected] quoting the job title in the Subject line. We regret that only shortlisted candidates will be notified.