Data Architecture and Engineering
- Bachelor's degree or higher in Computer Science, Engineering, or a related field (or equivalent practical experience).
- 12+ years of total and 10+ year progressive experience in data engineering, data architecture, and technical roles.
- Good understanding of Banking and Financial Services domains, including familiarity with enterprise analytics data assets.
- Experience in client consulting on data architecture and engineering solutions, with demonstrated ability to translate business needs into technical requirements.
- Demonstrated expertise in distributed data architecture, cloud data architecture, modern business intelligence (BI) tools, and frameworks/packages used for Generative AI and machine learning model development.
- Strong appreciation for data science concepts, including hands-on experience with machine learning algorithms, feature engineering, and model evaluation techniques.
- Excellent presentation, communication, and interpersonal skills, with the ability to effectively engage stakeholders at various organizational levels.
- Demonstrated aptitude for rapid learning and adoption of emerging technologies, methodologies, and paradigms in the evolving data science landscape.
- Proven ability to integrate new techniques and technologies to address complex business challenges and drive innovation.
- Strong resource planning, project management, and delivery skills.
- Proven experience designing and developing large-scale, production-grade systems utilizing best-in-class software engineering practices, including DevOps, CI/CD pipelines, and automation technologies.
- Good appreciation of data governance topics such as metadata management, data quality management, master data management and data security management.
- Experience with marketing cloud solutions such as Salesforce will be an advantage.
