Executive Data Engineer

·        2-6 Years of Experience in big data technologies, specifically Spark, Python, Hive, SQL, Presto (or other query engines), big data storage formats (e.g., Parquet, Avro or Any), orchestration tools (e.g., Apache Airflow, Control M) 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, Inhouse ETL tool, or any ETL tool experience).

·        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 Any cloud environments AWS,GCP,Azure(preferably AWS), with a solid understanding of core cloud concepts and services (e.g., EC2, S3), as well as Linux and containerization technologies (such as Docker and Kubernetes).

·        Exposure to AI-enabled tools, platforms, or solutions that can help automate operational processes, improve engineering productivity, and enhance day-to-day ways of working.

·        A background in solution delivery within the finance or treasury business domains, particularly in areas such as Liquidity or Capital, is advantageous.