Remote Senior Data Engineer

About Us Capital Bank N.A. is headquartered in Maryland and has been serving our communities since 1999. We stand as a publicly traded company (NASDAQ: CBNK) with over $3 billion in assets. We offer commercial and consumer banking services to clients primarily in Maryland, DC, and Northern Virginia, alongside two nation-wide lending brands; Capital Bank Home Loans and OpenSky, a credit card division that offers and services credit cards across all states.

Our personalized approach to banking, paired with cutting-edge technology solutions and a comprehensive suite of products and services, fuels our growth, and enables us to support our customers at every stage in their financial journey. Come join a bank where our employees thrive and are engaged in meaningful work. For the last 6 out of 7 years, Capital Bank was named one of the "Best Banks to Work For" in the U.S. by American Banker.

Position Purpose As part of the Technology team, the Senior Data Engineer will act as a subject matter expert (SME) responsible for managing, designing, and optimizing enterprise data pipelines and database solutions that support all lines of business at Capital Bank, including our Commercial Bank, Consumer Card division, and Mortgage division. This role owns end-to-end delivery and operations across our primary technology stack (Azure, SQL Server, and Snowflake), ensuring scalable, secure, and high-performance data platforms, reliable integrations with enterprise systems, and strong data governance. The Senior Data Engineer will build and optimize ETL/ELT processes, data lake and data warehouse solutions, and data transfer/file processing workflows to enable trusted analytics and reporting across the bank.

Position Responsibilities Serve as the expert for ETL and DB solutions, collaborating with business stakeholders and IT teams to define requirements, gather data, and implement optimized data solutions. Design, implement, and maintain data systems in Snowflake to ensure data scalability and accessibility. Implement and manage data lakes and data warehouses, creating pipelines and data models to enable efficient analytics and reporting.

Establish and document strategies for managing data transfer processes, including secure file transfers (SFTP), batch data processing, and real-time streaming. Build and optimize ETL pipelines for data extraction, transformation, and loading into operational databases or analytical platforms. Integrate and support data visualization tools such as Power BI, Sisense, Google Looker, Tableau, or similar platforms to enable actionable insights for business stakeholders.

Develop and maintain optimized data models for dashboards and reporting, ensuring compatibility with visualization tools. Plan, coordinate, and implement database migrations, upgrades, and patches with minimal downtime. Define and enforce database governance policies, including data integrity, security, and compliance with regulatory requirements.

Analyze and resolve database performance issues by optimizing queries, indexes, and schema designs. Partner with vendors to evaluate, select, and implement database tools, services, and technologies; stay informed about product roadmaps and industry trends. Develop disaster recovery and high-availability solutions, including replication, clustering, and failover.

Minimum Education