Senior Data Engineer

Capital Bank N.A. is a publicly traded company providing commercial and consumer banking services. The Senior Data Engineer will manage and optimize enterprise data pipelines and database solutions, ensuring high-performance data platforms and reliable integrations across the bank's various divisions.

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

Requirements:

• Bachelor's degree or higher in Computer Science, Information Systems, or a related field
• 6+ years of experience in data engineering, ETL, database management with experience in cloud-based databases and financial services preferred
• Experience in Database Administration (DBA), managing and optimizing databases for performance and security
• 3+ years of experience designing and building data lakes and data warehouses using platforms like Azure Fabrik, Snowflake, Amazon Redshift, or Google BigQuery
• 2+ years of experience using data visualization tools like Power BI, Sisense, Google Looker, Tableau, or similar platforms
• Experience with managing data transfers and file processes, including SFTP, secure data pipelines, and real-time or batch data movement
• Experience in proactively identifying, addressing, and monitoring data quality issues, adhering to established data quality standards
• Excellent communication skills and the ability to collaborate effectively across teams and stakeholders, explain technical concepts to non-technical stakeholders
• Expertise in cloud-based database platforms, such as Azure SQL, Amazon RDS, Google Cloud Spanner, and Snowflake
• Strong knowledge of data lake and data warehouse architectures, including designing efficient schemas, partitioning strategies, and optimizing storage
• Proficiency with data integration tools and technologies, such as Apache Kafka, Apache Spark, Talend, or Informatica
• Hands-on experience building and maintaining ETL pipelines to support large-scale data environments
• Advanced SQL skills and familiarity with programming languages like Python or Java for data manipulation and automation
• Experience with data visualization platforms, including building and optimizing dashboards using Sisense, Power BI, Google Looker, Tableau, or similar tools
• Experience with CI/CD tools (e.g., GitLab, Azure DevOps, Jenkins) and data pipeline monitoring tools (e.g., Airflow, Apache NiFi, Azure Data Factory)
• Strong understanding of database security best practices, including encryption, access controls, and compliance with regulatory standards
• Ability to manage data file transfers and processing workflows effectively
• Experience with database monitoring and performance tuning in cloud and hybrid environments
• Preferred experience in understanding data relationships, as well as developing and optimizing SQL queries, stored procedures, and database functions in both OLTP and OLAP systems
• Strong organizational and problem-solving skills in Agile or fast-paced environments