Capital Bank is looking for an experienced Data Engineer who is expected to build high quality data pipelines driving analytic solutions. The role requires deep understanding of data architecture, data engineering, data analysis, reporting, and a basic understanding of data science techniques and workflows. The data engineer is a skilled data / software engineer with experience creating data products supporting analytics. The candidate should possess strong problem-solving skills, work as part of a technical, cross functional analytics team, and solve complex data problems and deliver the insights to enable analytics strategy.

Role and Responsibilities:

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.

Qualifications & Competencies:

• 3+ years or more of work experience in data management disciplines including data integration, modeling, optimization, and data quality, and/or other areas directly relevant to data engineering responsibilities and tasks.
• At least one year of experience working in cross-functional teams and collaborating with business stakeholders in support of a departmental and/or multi-departmental data management and analytics initiative.
• A bachelor's degree in computer science or a related quantitative field.
• The ideal candidate will have a combination of IT skills, data governance skills, and analytics skills.