Sobre esta vaga de Staff Engineer - Data Engineering na Early Warning Services
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
Kubernetes experience
Physical Requirements
Working conditions consist of a normal office environment. Work is primarily sedentary and requires extensive use of a computer and involves sitting for periods of approximately four hours. Work may require occasional standing, walking, kneeling and reaching. Must be able to lift 10 pounds occasionally and/or negligible amount of force frequently. Requires visual acuity and dexterity to view, prepare, and manipulate documents and office equipment including personal computers. Requires the ability to communicate with internal and/or external customers.
Employee must be able to perform essential functions and physical requirements of position with or without reasonable accommodation.
The above job description is not intended to be an all-inclusive list of duties and standards of the position.
The base pay scale for this position in:
Phoenix, AZ/ Chicago, IL in USD per year is: $124,000 - $165,000.
San Francisco, CA in USD per year is: $174,000 - $223,000.
Additionally, candidates are eligible for a discretionary incentive plan and benefits.
This pay scale is subject to change and is not necessarily reflective of actual compensation that may be earned, nor a promise of any specific pay for any specific candidate, which is always dependent on legitimate factors considered at the time of job offer. Early Warning Services takes into consideration a variety of factors when determining a competitive salary offer, including, but not limited to, the job scope, market rates and geographic location of a position, candidate’s education, experience, training, and specialized skills or certification(s) in relation to the job requirements and compared with internal equity (peers). The business actively supports and reviews wage equity to ensure that pay decisions are not based on gender, race, national origin, or any other protected classes.
Early Warning Services is an affirmative action and equal opportunity employer.
Some of the Ways We Prioritize Your Health and Happiness
Healthcare Coverage – Competitive medical (PPO/HDHP), dental, and vision plans as well as company contributions to your Health Savings Account (HSA) or pre-tax savings through flexible spending accounts (FSA) for commuting, health & dependent care expenses.
401(k) Retirement Plan – Featuring a 100% Company Safe Harbor Match on your first 6% deferral immediately upon eligibility.
Paid Time Off – Flexible Time Off for Exempt (salaried) employees, as well as generous PTO for Non-Exempt (hourly) employees, plus 11 paid company holidays and a paid volunteer day.
12 weeks of Paid Parental Leave
Maven Family Planning – provides support through your Parenting journey including egg freezing, fertility, adoption, surrogacy, pregnancy, postpartum, early pediatrics, and returning to work.
And SO much more! We continue to enhance our program, so be sure to check our Benefits page here for the latest. Our team can share more during the interview process!
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Early Warning Services, LLC (“Early Warning”) considers for employment, hires, retains and promotes qualified candidates on the basis of ability, potential, and valid qualifications without regard to race, religious creed, religion, color, sex, sexual orientation, genetic information, gender, gender identity, gender expression, age, national origin, ancestry, citizenship, protected veteran or disability status or any factor prohibited by law, and as such affirms in policy and practice to support and promote equal employment opportunity and affirmative action, in accordance with all applicable federal, state, and municipal laws. The company also prohibits discrimination on other bases such as medical condition, marital status or any other factor that is irrelevant to the performance of our employees.
