Senior Data Engineer

About the role

The Senior Data Engineer is a subject‑matter expert on the Technology team responsible for designing, building, and operating enterprise‑scale data pipelines, lakes, warehouses and database solutions across Capital Bank’s commercial, consumer card and mortgage divisions, using Azure, SQL Server and Snowflake to deliver secure, high‑performance data platforms, integrations and governance.

About the company

Capital Bank N.A. is a publicly traded (NASDAQ: CBNK) bank headquartered in Maryland with over $3 billion in assets, offering commercial and consumer banking services in Maryland, DC and Northern Virginia, plus nationwide Home Loans and OpenSky credit card brands. The bank emphasizes a personalized approach, cutting‑edge technology, and community‑focused growth, and has been named a “Best Bank to Work For” for six of the last seven years.

Requirements

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