Sr. Staff Data Engineer

At Early Warning, we’ve powered and protected the U.S. financial system for over thirty years with cutting-edge solutions like Zelle®, Paze℠, and so much more. As a trusted name in payments, we partner with thousands of institutions to increase access to financial services and protect transactions for hundreds of millions of consumers and small businesses.

Positions located in Scottsdale, San Francisco, Chicago, or New York follow a hybrid work model to allow for a more collaborative working environment.

Candidates responding to this posting must independently possess the eligibility to work in the United States, for any employer, at the date of hire. This position is ineligible for employment Visa sponsorship.

Overall Purpose

This position is a key role in the development, test, and deployment of complex solutions.

Essential Functions

• Partners with software engineering, product, and architecture to shape engineering approaches, share knowledge and experience.

• Own the data and technical strategy for broad or complex requirements with insightful and forward-looking approaches that go beyond the direct team and solve large open-ended problems.  

• Responsible for department-wide design, patterns and code approaches.

• Reviews and validates effectiveness of code output from multiple teams.

• Accountable for resolving technical conflict within and between multiple teams.

• Drive all aspects of technical architecture, design, prototyping and implementation in support of both product needs as well as overall technology and data strategy.

• Represent engineering in cross-functional team sessions and able to present sound and thoughtful arguments to persuade others. Adapts to the situation and can draw from a range of strategies to influence people in a way that results in agreement or behavior change

• Collaborate and partner with product managers, designers, and other engineering groups to conceptualize, build new features and create product descriptions.

• Actively own features or systems and define their long-term health, while also improving the health of surrounding systems.

• Assist Support and Operations teams in identifying and quickly resolving production issues.

• Develop and implement tests for ensuring the quality, performance, and scalability of our application.

• Develop and mentor other engineers.  May serve as a technical leader for cross-functional projects.

• Actively seeks out ways to improve engineering standards, tooling, and processes.

• Supporting the company’s commitment to risk management and protecting the integrity and confidentiality of systems and data.

Minimum Qualifications

• Education and/or experience typically obtained through a Bachelor’s degree in computer science or related technical field.

• Twelve or more years of relevant related experience.

• Nine or more years of experience in the development of complex database management systems, Business Intelligence solution, AI/ML Model development & Oprationization (includes feature engineering, model optimization, model operationization), distributed systems, SaaS, cloud solutions, micro services.

• Hands-on Docker experience.

• Two or more years of experience in the development of end to end data management platforms – data modeling, data goveranace, BI Reporting, AI/ML model life cycle management.

• Five or more years of work experience with ETL development (using Ab Initio, Talend, Informatica or other industry proven tools), BI Reporting design & development (using Tableu or Business Objects or Griffana or other industry tools).

• One or more years ML Development (using Python, PySpark, Spark), ML Model development framework (using PyCharm, SciKit, Sage Maker, Tensorflow).

• Demonstrated experience in delivering business-critical systems to the market.

• Ability to influence and work in a collaborative team environment across multiple departments.

• Experience designing/developing scalable systems.

• Experience with event-driven architecture and messaging frameworks (Pub/Sub, Kafka, RabbitMQ, etc).

• Working experience with cloud infrastructure (Google Cloud Platform, AWS, Azure, etc).

• Knowledge of mature engineering practices (CI/CD, testing, secure coding, etc).

• Knowledge of Software Development Lifecycle (SDLC) best practices, software development methodologies (Agile, Scrum, LEAN etc) and DevOps practices.

• Background and drug screen.

<