The candidate's role in collaborating with operational experts and data strategists, building insightful data tools, and delivering valuable data assets to the team and wider business. The opportunity to contribute significantly to data-promotion initiatives and enhance business intelligence capabilities is also highlighted. Posting Description The Instrument Reference Data team is part of the wider Data Solution Operations team in the Securities Services Organization. Having accessible data insights and analytic capabilities is crucial to drive the business and operations forward. It facilitates identification of opportunities in operational process and themes to curate strategies. The Data Engineer designs, builds and maintain these capabilities. As the Data Engineer in our Business Intelligence & Analytics team, you will work with Operation SMEs in and data strategist to building data insights and tools, delivering data assets that add value to the team and the business. This role not only seeks technical proficiency but also requires strong analytical and communication skills to collaborate with cross-functional global teams. Job responsibilities Design, develop, maintain and deploy visualizationsto empower reference data team and clients, embedding good UX design to enable intuitive sharing of data insights. Leveraging Python/SQL to understanding database design, relationships and logic to source data for visualizations Ensure all elements are automated and executing in controlled environment and has appropriate documentation Develop and maintain AI/ML models to achieve desired business outcomes Manage end to end projects, understand business requirements and devise approaches Manage and drive data quality initiatives which includes change management, data analytics and data quality related projects Derive insights from dashboards and identify data quality themes and work with stakeholders to curate strategies to address them. Perform problem and root-cause analysis to identify and refine inefficiencies to improve data quality, and deliver value to our stakeholders. Required qualifications, capabilities and skills Applicants must have a Bachelor's degree (in Finance, Science or Technology) or equivalent Minimum 3 years of proven experience in data modelling, data transformation and visualization. At least 2+ years of work experience in Financial Services is required Should have hands on experience in developing end to end BI solutions using digital tools like JIRA/Confluence, Python, Alteryx, Tableau/Qlik/Power BI and AWS Knowledge of machine learning techniques like Natural Language Processing, Clustering, Deep Learning and advanced statistical techniques and concepts. Demonstrate ability to communicate effectively within a team and across departments, able to drive conversations to extract the require details Strong analytical and problem solving skills with attention to details to formulate effective strategies and solutions to address pain points and improve efficiency Advanced experience in design, develop, maintain and deploy visualizations using PowerBI/Tableau/Qlik Advanced experience in writing advance SQL and Python queries/code, employing AI tools for BI&A Strong understanding of data management principles for financial services governance, quality, storage, modelling, etc. Strong knowledge of financial instruments, corporate action events and data vendors (Bloomberg, Refinitiv, ICE, MSCI, etc)
