AirflowAmazon RedshiftApacheAWSCloudPythonSQLData EngineeringData WarehousingData LakeRedshiftApache AirflowdbtAmazon Web ServicesS3GitGitHubVersion ControlCI/CDRemote Work
About this role
Role Overview
Support the Bank’s “People First” focus and rules of engagement—maintaining a professional demeanor, working as an active member of the CNOB team, providing clients excellent service, always striving to make CNOB “A Better Place to Be”
Architect, build, and maintain data pipelines using Apache Airflow, ensuring seamless data movement across AWS S3 and Amazon Redshift.
Design and implement scalable data models using dbt Labs, transforming raw data into clean datasets optimized for analytical querying.
Facilitate the setup of new data sources, designing the architecture to securely and efficiently ingest data from third-party APIs, transactional databases, and external platforms into the data lake/warehouse.
Maintain a deep understanding of the underlying data model to troubleshoot bottlenecks, optimize Redshift query performance, and implement rigorous data quality testing and alerting.
Serve as a subject matter expert on data architecture, establishing best practices for code reviews, version control, and CI/CD workflows within the data engineering team.
Requirements
Strong “People First” interest and ability.
Comprehensive understanding of cloud computing principles and cloud-native data architectures, specifically within the Amazon Web Services (AWS) ecosystem.
Deep knowledge of modern data warehousing concepts, including schema design and data modeling methodologies.
Understanding of data governance, data privacy regulations, and enterprise security best practices.
Expert-level proficiency in SQL and Python.
Hands-on mastery of dbt Labs, Apache Airflow, Amazon Redshift, and AWS S3.
Strong proficiency with version control systems (Git/GitHub) and command-line interfaces.
7+ years of progressive, dedicated experience in Data Engineering, Data Architecture, or a heavily overlapping software engineering field.
The ability to quickly dissect complex pipeline failures, identify root causes in underlying data, and implement permanent solutions.
The aptitude to listen to non-technical stakeholders, understand their analytical needs, and translate those needs into technical data structures.
The capacity to thrive in a remote work environment, managing time effectively, and driving large-scale projects from conception to deployment with minimal oversight.
A natural meticulousness required to ensure absolute data accuracy and system reliability.
Tech Stack
Airflow
Amazon Redshift
Apache
AWS
Cloud
Python
SQL
Benefits
World class health, vision, and dental benefits on day one