Staff Engineer - Data Engineering

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 provides senior technical leadership and hands on work in the architecture, design, development, testing, and deployment of complex data platforms and data-driven solutions. The role partners across engineering, product, and data teams to define technical strategy, solve large-scale and open-ended problems, and deliver scalable, reliable solutions from concept through production. This is a hands-on role where 50+% of time will be spent coding and design.

Essential Functions

• Drive technical and data architecture, design, prototyping, and implementation in support of product needs and the broader technology and data strategy.
• Provide technical leadership in developing technical plans and backlogs and drive execution from design and development through production delivery.
• Own features, platforms, or systems and define their long-term health, reliability, scalability, and maintainability while improving surrounding systems.
• Partner with Support and Operations teams to identify, troubleshoot, and quickly resolve production issues.
• Develop and implement testing strategies to ensure application quality, performance, reliability, and scalability.
• Identify and drive improvements to engineering and data standards, tooling, development practices, and processes.
• Support the company’s commitment to risk management and to protecting the integrity, availability, and confidentiality of systems and data.

Minimum Qualifications

• Education and/or experience typically obtained through a bachelor’s degree in computer science or a related technical field.
• Typically, eight or more years of relevant professional experience.
• Seven or more years of experience developing complex data platforms, distributed systems, SaaS solutions, cloud-based solutions, and/or microservices.
• Six or more years of experience developing data warehouse, data lake, lakehouse, and big data platforms, including structured and unstructured data, real-time and batch processing, and data standards.
• Two or more years of experience developing and/or operationalizing Artificial Intelligence or Machine Learning models, including feature engineering, data pipelines, model deployment, operationalization, and monitoring.
• Demonstrated experience delivering business-critical systems to production.
• Experience designing and developing scalable, highly available systems.
• Extensive experience implementing modern data warehouse solutions using technologies such as Snowflake, including dimensional modeling, star and snowflake schemas, performance optimization, and scalable data processing.
• Experience designing and implementing modern data lake and lakehouse architectures using Databricks, Apache Iceberg, Amazon S3 or equivalent technologies.
• Experience developing scalable ETL/ELT, data integration, and reusable data processing frameworks.
• Experience implementing data engineering, data science, or analytics solutions using Python, PySpark, Apache Spark, Databricks, Snowflake, or equivalent tools.
• Experience with event-driven architecture and messaging frameworks such as Amazon SNS, Amazon SQS, Amazon Kinesis, Apache Kafka, or equivalent technologies.
• Working experience with AWS cloud infrastructure and services, including scalable compute, storage, networking, security, and data services.
• Experience with Infrastructure as Code (IaC) and AWS infrastructure provisioning using Terraform or equivalent technologies.
• Knowledge of mature engineering practices, including CI/CD, automated testing, secure coding, code quality standards, and automated infrastructure deployment.
• Knowledge of Software Development Lifecycle best practices, software development methodologies such as Agile, Scrum, and Lean, and DevOps practices.
• Strong attention to detail.
• Background and drug screen.

Preferred Qualifications

• Master’s or doctoral degree in computer science, data science, engineering, or a related technical field.
• Deep experience designing and operating large-scale AWS-based data platforms.
• Strong hands-on experience with Databricks, including scalable data processing, data pipelines, workload optimization, and lakehouse architecture.
• Strong hands-on experience with Snowflake, including data modeling, ingestion, performance optimization, workload management, and enterprise-scale data warehouse architecture.
• Experience integrating Databricks and Snowflake within modern enterprise data architectures.
• Experience with modern open table formats and lakehouse technologies such as Apache Iceberg and Delta Lake.
• Experience designing and operating cloud-based data lake and object-storage solutions using Amazon S3.
• Strong programming experience with Python, PySpark, and Apache Spark.
• Experience implementing AWS infrastructure using Terraform and Infrastructure as Code practices.
• Experience with AWS data and analytics services such as Amazon S3, AWS Glue, Amazon Airflow , Amazon Kinesis, Amazon Redshift, AWS Lambda, and Amazon Athena.
• Experience with data governance, cataloging, lineage, metadata management, and data quality capabilities across Databricks, Snowflake, and AWS.
• Experience with monitoring, alerting, logging, and observability for cloud-based data platforms.
• Kubernetes and container orchestration experience, including Amazon EKS.
• Experience designing and operating event-driven, streaming, and real-time data architectures using AWS services and technologies such as Kinesis and Kafka.
• FinTech or payments industry 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.

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

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.

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.