Staff Engineer - Data Engineering

About this role

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

We're looking for a Staff Data Engineer to help build and evolve the modern data platform behind Zelle, one of the largest digital payments networks in the U.S. This role is perfect for an engineer who enjoys solving large-scale distributed data challenges, influencing architecture, and building cloud-native data platforms that powers next generation Payment products, analytics, and supports AI/ML workloads.

You'll work with modern technologies in AWS cloud while partnering with Product, Architecture, and Platform Engineering to deliver reliable, secure, and scalable data capabilities. If you're passionate about building reusable platform solutions, driving technical excellence, and making an impact at enterprise scale, we'd love to talk to you.

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

• Participate in the strategic development of methods, techniques, and evaluation criteria for projects and programs.

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

• Provide leadership and technical expertise in support of building a technical plan and backlog of stories, and then follow through on execution of design and build process through to production delivery.

• Guide a broad functional area and lead efforts through the functional team members along with the team’s overall planning.

• 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 and 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.

• Actively seek out ways to improve engineering and data 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.

• Eight or more years of relevant related experience

• Seven or more years of experience in the development of complex data platform, distributed systems, SaaS, cloud solutions, micro services.

• Six or more years of experience in the development of Data Warehouse, Big Data – structured & unstructured platforms, real-time & batch processing, data standards.

• Four or more years of experience in development of Business Intelligent Solutions

• Two or more years of experience in development / operationalization of Artificial Intelligence / Machine Learning Models / Model development life cycle activities (implementing feature engineering, data pipelines, model operationalization, model monitoring).

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

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

• Experience designing/developing scalable systems.

• Extensive experience implementing Data Warehouse (Star / Snow flake schemas) using SQL Server or equivalent, Big Data – HDFS, Elastic Search, ETL process development using IBM Infosphere or equivalent, Reusable Frameworks

• Experience with implementing data science solutions using Python, Spark, PySpark, R, Data Robot.

• 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.

• Attention to detail

• Background and drug screen.

      Preferred Qualifications • MS or PHD

• Experience using AI/ML Model Frameworks like Tensorflow, Sage Maker, Scikit, PyCharm

• Big Data Platforms (Cloudera, S3)

• Database platforms (Oracle, SQL Server) with experience around performance aspects and replication

• Computer language experience (Python, PySpark, and R)

• Knowledge of Aerospike, Scality S3, Elastic Search

• Monitoring and Alerting systems experience (AppDynamics) or other observability measures

• Knowledge of ACH/EFT

• Knowledge of real time payment networks (RTP, FedNow) 

• Experience in development / operationalization of Artificial Intelligence / Machine Learning Models / Model development life cycle activities (implementing feature engineering, data pipelines, model operationalization, model monitoring).

• FinTech experience

• Kubernet

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