Bank al Etihad - Careers Day
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Senior Associate , Banking Intelligence

Job Description and Requirements

This Role for taking the lead in technical architecture, to design and build out the data engineering platform that will form the nucleus of the Analytics, BI and Machine Learning initiatives for Banking Business. The role will involve building and maintaining database solutions that are used for daily reporting and drive business decision making while dealing efficiently with the massive scale of data available through Data Warehouse. Also responsible for designing and implementing solutions that involve data interfaces with both internal and external systems using third-party and in-house reporting tools, modeling metadata, building reports and dashboards, and administering the platform software. Responsible for developing , maintaining , testing and evaluating big data solutions within the Bank.


Job Resposnsibilities:


  • Work closely with the analysts and business stakeholders to gather technical requirements.
  • Provide data insights for product management and marketing decision making.
  • Participate in “deep-dive” research projects, such as detailed product analysis, customer segmentation or lifetime value analysis.
  • Build new data views, aggregations, dashboards and predictive models.
  • Contributing at a senior-level to the data warehouse design and data preparation by implementing a solid, robust, extensible design that supports key business flows.
  • Performing all of the necessary data transformations to populate data into a warehouse table structure that is optimized for reporting.
  • Establishing efficient design and programming patterns for engineers as well as for non-technical peoples.
  • Designing, integrating and documenting technical components for seamless data extraction and analysis on big data platform.
  • Ensuring best practices that can be adopted in Big Data stack and share across teams and BUs.
  • Providing operational excellence through root cause analysis and continuous improvement for Big Data technologies and processes and contributes back to open source community.
  • Contributing to innovations and data insights.
  • Build new data views, aggregations, dashboards and predictive models.