Experience in Big Data technologies, specifically Spark, Python, Hive, SQL, Presto (or other query engines), big data storage formats (e.g., Parquet), orchestration tools (e.g., Apache Airflow) and version control (e.g. Bitbucket)
Proficiency in developing configuration-based ETL pipelines and user-interface driven tools to optimize data processes and calculations (e.g., Dataiku).
Experience in analysing business requirements, solution design, including the design of data models, data pipelines, and calculations, as well as presenting solution options and recommendations.
Experience working in a cloud-based environment (ideally AWS), with a solid understanding of cloud computing concepts (EC2, S3), Linux, and containerization technologies (Docker and Kubernetes).
A background in solution delivery within the finance or treasury business domains, particularly in areas such as Liquidity or Capital, is advantageous.
Additional pointers:
We are seeking for a mid-level engineer to design and build Liquidity calculations using our bespoke Data Calculation Platform (DCP), based on documented business requirements.
The front-end of the DCP is Dataiku, but prior experience with Dataiku is not necessary if they've had experience working as a data engineer.
Liquidity experience is not necessary, but it would be helpful if they've had experience designing and building to business requirements.
There is a requirement to work 3 days in the office in Gurugram.
They will work as part of a team that is located in both Sydney and Gurugram.
The reporting manager will be based in Gurugram and project leadership in Sydney.

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