Full job description that includes: Mandatory skills: SQL, Cucumber Gherkin, ALM, MS Office, Python 3.0, Jira, Jama, Confluence, Sharepoint, Microstrategy, SAP Business Object, DQIM Domain Credit Risk Management (understanding of Regulatory Capital Adequacy under Basel 2, 3, Fed Reserve SR letters, CRD, BCBS239 covering ACS and Internal Stress Testing, Securitisations and OTCs exposures NMR, Market and CCR treated under SACCR, VaR, sVaR, RWA, CVA, FRTB, Wholesale metrics, VaR models, Risk Engine, Trade workflow, mapping, CCR, MR Regulatory reporting, PnL) Nice to have skills: Microstrategy, Python, Databricks Responsibilities Gather business requirements, determine data and reporting insights and findings, build datasets and support Tableau Reports/Dashboards development Develop multiple complex SQL queries and views (pulling from complex, multiple data sources, synthesizing and formatting to prepare for distribution to stakeholders) Support end-to-end Business Intelligence lifecycle development processes as needed, which includes, but is not limited to, capturing business requirement definitions (BRD/user stories), creating functional requirement definitions (FRD), technical design documents (TDD), and running user acceptance testing (UAT) Power business strategy and execution by building clever system integrations Maintain reliable data pipelines and architect scalable data solutions Collaborate closely with Finance and IT to establish optimized, source-of-truth datasets for cross-functional reporting Requirements: Bachelor's Degree (Technology related field) or equivalent work experience. 12 relevant years' experience in assembling, querying large, complex sets of data and building datasets for visualizations that meet business requirements Design and develop interactive Tableau Dashboards and Reports providing actionable insights or any other visualization tools Excellent coding skills in SQL with experience in creating curated datasets from different data sources Collaborate with Data Engineers to integrate various data sources into Tableau ensuring data accuracy and data integrity Provide a clear path to the automation of metrics and data to the business stakeholders with a clear articulation of dependencies and asks Strong understanding of applied machine learning topics Ability to explain complex, technical subjects to non-technical audiences Consistent track record of leading complex data projects Values documentation, collaboration, and mentoring
