Data Engineer

Technical data development

• Collect, blend, and transform data using ETL tools (Informatica Data Integration), data warehousing systems (IBM Netezza), and code development (e.g., SQL, Pyhton).
• Design, develop, optimize, and maintain data architecture and pipelines that adhere to ETL principles and business goals.
• Create data products for analytics and data science team members to improve their productivity.
• Lead the evaluation, implementation and deployment of emerging tools and process for analytic data engineering to improve our productivity as a team.
• Partner with BI analysts and solutions architects to develop technical architectures for strategic banks projects and initiatives.
• Learn about key data technical topics covering machine learning, data science, computer vision, artificial intelligence, statistics.
• Implement data models and structure data in ready-for BI consumption formats.
• Perform aggregations on data across various warehousing models for BI purposes.

Business collaboration

• Improve the data availability by acting as a liaison between business and source systems.
• Solve complex data problems to deliver insights that helps our business to achieve their goals.
• Advise, consult, mentor and coach other data and analytic professionals on data standards and practices.
• Develop and deliver communication and education plans on analytic data engineering capabilities, standards, and processes.