Staff Engineer - Data Engineering at Early Warning® | AZ, US | Rezi

Staff Engineer - Data Engineering at Early Warning®

Staff Engineer - Data Engineering

Early Warning® · AZ, US

Yesterday

Staff Engineer - Data Engineering

Early Warning® · AZ, US

2 days ago
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About the Role

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

Responsibilities

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

Requirements

  • 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.

Skills

  • Data strategy
  • Technical and data architecture
  • Design
  • Prototyping
  • Implementation
  • Technical plan and backlog development
  • Cross-functional collaboration
  • Feature ownership
  • System health management
  • Production issue resolution
  • Test development
  • Quality assurance
  • Performance testing
  • Scalability testing
  • Engineering standards improvement
  • Data standards improvement
  • Tooling improvement
  • Process improvement
  • Risk management
  • Data confidentiality
  • Data integrity
  • Data Warehouse (Star / Snow flake schemas)
  • SQL Server
  • Big Data (HDFS, Elastic Search)
  • ETL process development (IBM Infosphere)
  • Reusable Frameworks
  • Data science solutions (Python, Spark, PySpark, R, Data Robot)
  • Event-driven architecture
  • Messaging frameworks (Pub/Sub, Kafka, RabbitMQ)
  • Cloud infrastructure (Google Cloud Platform, AWS, Azure)
  • CI/CD
  • Testing
  • Secure coding
  • Software Development Lifecycle (SDLC)
  • Agile
  • Scrum
  • LEAN
  • DevOps practices
  • MS or PHD
  • AI/ML Model Frameworks (Tensorflow, Sage Maker, Scikit)
  • PyCharm
  • Big Data Platforms (Cloudera, S3)
  • Database platforms (Oracle, SQL Server)
  • Aerospike
  • Scality S3
  • Elastic Search
  • Monitoring and Alerting systems (AppDynamics)
  • Observability measures
  • ACH/EFT
  • Real time payment networks (RTP, FedNow)
  • FinTech
  • Kubernetes
  • HBase
  • Hive
  • Solr
  • Spark/Scala programming
  • Amazon S3
  • AWS Cloud
  • Databricks
  • Snowflake

Location

  • Scottsdale
  • San Francisco
  • Chicago
  • New York

Work Type

  • Hybrid

Experience Level

  • 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).

Education Level

  • Bachelor’s degree in computer science or related technical field
  • MS or PHD

Salary/Compensations

  • $124,000 - $165,000 (Phoenix, AZ)
  • $174,000 - $223,000 (San Francisco, CA)

Benefits

  • Discretionary incentive plan
  • Healthcare Coverage – Competitive medical (PPO/HDHP), dental, and vision plans
  • 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.

About the Company

  • 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.

Equal Opportunity

  • 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.
  • Early Warning Services is an affirmative action and equal opportunity employer.
  • 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.