To be considered for the role, you must meet the below requirements:
Qualifications:
In a relevant field such as Computer Science, Computational Mathematics, Computer Engineering or Software Engineering.
Specialization or electives in a Data & Analytics field (e.g. Data Warehousing, Data Science, Business Intelligence) a nice-to-have
Experience:
- 2+ years Data Engineering (Fewer years’ experience will be considered for Masters degree holders)
- Minimum 2+ years of development, testing and support experience in the analytic applications such as Data Lake and Data Warehouse (preferably using the Big Data stack and Microsoft Azure cloud infrastructure)
- Experience with batch or real-time data ingestion; experience with coding pipelines that handle massive quantities of data (structured and unstructured), securely and in a timely fashion
- Understanding of data architecture concepts such as data modelling, Big Data storage, Lambda architecture, data vault and dimensional modelling nice-to-have
- Understanding on integration with source systems; able to load operational systems’ data into a single data platform using data integration tools
- Experience scheduling jobs that can be monitored efficiently and ensure data quality
- Ability to conduct unit testing
- Strong SQL querying skills required
- Airline industry experience a nice-to-have
Knowledge/Skills:
- Strong ability to conduct data analysis (e.g. source system identification, data dictionary / metadata collection, data profiling, source-to-target mapping) is preferred
- Operates with a “You Code It, You Own It” mindset (i.e. supports the products they build)
- Demonstrated problem-solver; able to design and document solutions independently
- Team player; able to collaborate with others to remove blockers, solve complex design problems and debug/resolve issues
- Able to deliver solutions (and associated value) iteratively
- Is accountable and displays positive attitude
- Self-starter and has passion for exploring and learning new technologies, especially those in the Enterprise Data & Analytics space