Senior Data Platform Engineer (Cloud & AI)

Early Warning; Scottsdale (AZ); Hybrid; USD 175,000 - 225,000; Full time

Benefits offered by this job

Healthcare Coverage

401(k) Retirement Plan

Paid Time Off

Paid Parental Leave

Job summary

Early Warning is seeking a Staff Data Engineer to build and evolve the data platform behind Zelle and our digital payments network. The role focuses on large-scale distributed data challenges, cloud-native architectures, and enabling AI/ML workloads in AWS.

You will collaborate with product, architecture, and platform engineering to deliver reliable, secure data capabilities. You’ll influence architecture, own features and system health, and guide teams through design, prototyping, and

Qualifications

• Bachelor’s degree in computer science or related field.
• 8+ years of relevant experience in data platforms and distributed systems.
• 6+ years building data warehouses, real-time and batch processing.
• 2+ years exposing AI/ML model lifecycles and pipelines.
• Experience with SQL Server or equivalent and big data tech.
• Strong Python, Spark, PySpark, and data science tooling knowledge.

Responsibilities

• Lead data architecture and platform design for scalable systems.
• Drive technical plans and backlogs from conception to production.
• Collaborate cross-functionally with product and engineering teams.
• Own feature health and improve surrounding data systems.
• Develop tests to ensure performance and scalability.
• Improve data standards, tooling, and DevOps practices.

Skills

Data engineering

Distributed systems

Python

Spark

PySpark

SQL

Cloud AWS

Kubernetes

Big Data

Data Warehouse

Education

Bachelor’s degree in CS or related field

Tools

IBM Infosphere

Elastic Search

HDFS

S3

Kafka

Pub/Sub

CI/CD tooling

Job description

Early Warning is seeking a Staff Data Engineer to build and evolve the data platform behind Zelle and our digital payments network. The role focuses on large-scale distributed data challenges, cloud-native architectures, and enabling AI/ML workloads in AWS.

You will collaborate with product, architecture, and platform engineering to deliver reliable, secure data capabilities. You’ll influence architecture, own features and system health, and guide teams through design, prototyping, and