Data Engineer-Architecture
About The Position
This position reports to our Business Intelligence and Analytics Manager. The hire will be responsible for mentoring our team on industry best practices, as well as ensuring data pipelines solve business problems. The ideal candidate has a passion for data,and is willing to share that passion with others. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives. This individual will play a mission-critical role in building the internal data warehouse, ensuring secure and automated data pipelines, and enabling advanced analytics and AI across the enterprise. This role demands deep technical expertise, independent decision-making, and cross-functional collaboration to ensure our infrastructure is secure, compliant, efficient, and future-proof. You will be an empowering mentor who will be: A trusted expert A natural communicator of data solutions A champion for our members and the community A guide through the moments that matter the most to our members
Requirements
- Bachelor’s degree in Computer Science, Data Engineering, or related technical field.
- Minimum of 6 years of hands-on experience in data engineering, platform engineering, or related roles.
- Minimum of 2 years of experience mentoring or leading technical team members.
- Expert-level proficiency in SQL and Python for data processing and automation.
- Hands-on experience with cloud data platforms (AWS, Azure, or GCP), including storage, compute, and networking services.
- Production experience with data warehousing concepts: dimensional modeling, ELT/ETL pipelines, and MPP databases.
- Proficiency with Infrastructure-as-Code tools (Terraform, CloudFormation, or similar).
- Experience with containerization and orchestration (Docker, Kubernetes, Airflow, or similar).
- Strong problem-solving abilities with complex, distributed systems.
- Excellent communication skills for technical and non-technical stakeholders.
- Experience with agile development methodologies and collaborative workflows.
- Demonstrated ability to balance technical debt with feature delivery.
Nice To Haves
- Master’s degree or advanced certifications (AWS Certified Data Engineer, Google Cloud Professional Data Engineer).
- Financial services or regulated industry experience.
- Experience with modern data stack tools (dbt, Snowflake, Databricks, Airbyte).
- Open-source contribution history or technical blog or speaking experience.
Responsibilities
- Design, implement, and maintain scalable batch and real-time data ingestion pipelines supporting big data volumes of daily data processing.
- Develop and maintain automated data quality monitoring systems, achieving 99.5 percent data accuracy SLAs across critical business processes.
- Build and optimize cloud-based data infrastructure (AWS/Azure/GCP), including data warehouses, lakes, and processing frameworks.
- Define long-term data platform architecture strategy and evaluate new technologies for organizational adoption.
- Lead evaluation, selection, and implementation of data tools and platforms, managing vendor relationships.
- Mentor junior engineers and system analysts through code reviews, architecture discussions, and hands-on training.
- Participate in on-call rotation for critical data systems
- Identify and implement automation opportunities, reducing manual processes.
- Compliance with all Bank Secrecy Act (BSA) rules and regulations and the Customer Identification Program (CIP).
- Attends required annual BSA training and required compliance training.
- Assist with all other duties as assigned or identified.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
