Data Engineer II

Data Engineer II

This is a remote role that may only be hired in the following location(s): North Carolina, Arizona, Florida, and Texas.

We are seeking a motivated Data Engineer II to join our Data Platform Engineering Organization and help build scalable cloud-based data solutions that enable analytics and data-driven decision-making across the organization.

The ideal candidate is a hands-on data engineer with experience in cloud-based data platforms, data warehousing, ETL/ELT development, and modern data engineering practices. This individual will contribute to the development and support of scalable data pipelines, integrations, and data products utilizing AWS Services, Snowflake, dbt, Python, SQL, and related technologies. As part of our growing Cloud Data & AI Platform organization, you will collaborate with a talented team of engineers, product partners, and business stakeholders to modernize enterprise data platforms and deliver cloud-based data solutions that support critical business initiatives. This is an opportunity to work with modern technologies, solve complex data challenges, and contribute to the bank's data and AI transformation journey.

Duties and Responsibilities:

The successful candidate will thrive in a collaborative environment, possess strong problem-solving skills, and be passionate about building reliable, scalable, and high-quality data solutions.

• Design, build, and support scalable data pipelines and cloud-based data solutions utilizing AWS Services, Snowflake, dbt, Python, SQL, and related technologies.
• Implement data warehouse solutions, dimensional data models, and ETL/ELT processes that support reporting, analytics, and business intelligence capabilities.
• Implement data quality validations, test cases, and controls to ensure accurate, consistent, and reliable data assets.
• Develop and maintain data tests, including dbt tests, to support data quality and reliability requirements.
• Support workflow orchestration, monitoring, troubleshooting, log analysis, and production operations using Airflow and cloud-native technologies.
• Collaborate with business users, product partners, analysts, and technology teams to deliver data solutions that support business objectives.
• Follow established engineering standards, development practices, documentation requirements, and testing procedures to support high-quality solution delivery.
• Participate in pipeline deployments, environment promotion activities, operational support, and performance optimization efforts using established CI/CD processes.
• Leverage AI-powered development and productivity tools to improve engineering efficiency, code quality, and delivery outcomes.

Qualifications:

Bachelor's Degree and 2 years of experience in Data Engineering, Data Warehousing, Cloud Data Platforms, or related technology disciplines. OR High School Diploma or GED and 6 years of experience in Data Engineering, Data Warehousing, Cloud Data Platforms, or related technology disciplines.

Preferred Qualifications:

• Experience working with cloud-based data platforms and modern data processing technologies such as AWS, Snowflake, Spark, or equivalent solutions.
• Proficiency in Python and SQL with experience developing ETL/ELT processes, data pipelines, and data integration solutions.
• Experience utilizing modern data engineering tools and frameworks such as dbt, Apache Airflow, or similar technologies.
• Experience contributing to the delivery and support of scalable, reliable data solutions in enterprise environments.
• Experience collaborating with business and technology stakeholders to deliver data-driven solutions.
• Strong analytical, problem-solving, and communication skills.

Additional Qualifications are a plus:

• Experience with enterprise ETL/ELT tools such as DataStage, SAP BODS, SSIS, Informatica, or equivalent technologies.
• Experience with Operational Data Stores (ODS), analytics platforms, and data products.
• Experience working with cloud-based and on-premises data environments.
• Exposure to Data Vault modeling and modern data warehousing methodologies.
• Understanding of data governance, security, compliance, and data quality management practices.
• Experience within Financial Services, Banking, or other highly regulated industries.
• Familiarity with Tableau, Power BI, or other analytics and visualization platforms.
• Experience using AI-powered development and productivity tools to improve engineering efficiency and delivery outcomes.
• AWS Certified Cloud Practitioner, AWS Certified Developer – Associate, AWS Certified Data Engineer – Associate, SnowPro Core Certification, or equivalent cloud and data platform certifications.