Lead Software Engineer, Identity

zetaglobal; United States; Remote; USD 150,000 - 200,000; Full time

Benefits offered by this job

Unlimited PTO

Medical insurance

Dental insurance

Vision insurance

Employee equity

Discounts

Wellness classes

Pet insurance

Job summary

zetaglobal is seeking an experienced backend/data engineer to lead engineering for identity services and large-scale data processing. You will design APIs, build event-driven pipelines, and operate cloud-native services on Kubernetes.

The role emphasizes reliability, speed, and transparent data handling across teams. Candidates should have 5+ years in backend/data engineering, strong Python/Java/Scala skills, and hands-on experience with Kafka, Spark/Hive/Flink, and Airflow/Luigi.

Qualifications

• Five+ years in backend or data engineering at scale.
• Proficiency in Python, Java, or Scala with APIs and distributed systems.
• Hands-on with Kafka or similar event platforms and data processing frameworks.
• Experience deploying on Kubernetes; familiarity with EKS, Helm, service meshes.
• Strong SQL, data modeling, and AWS cloud skills.
• Proven technical leadership, communication, and mentoring capabilities.

Responsibilities

• Design and build APIs and backend services for identity resolution and integrations.
• Develop and optimize high-volume event-driven pipelines and workflows.
• Deploy and operate cloud-native services on Kubernetes with repeatable deployments.
• Improve reliability, observability, scalability, and performance of data pipelines.
• Collaborate with product, engineering, and data teams to deliver end-to-end capabilities.
• Mentor engineers and influence architecture and roadmap decisions.

Skills

Backend engineering

Python/Java/Scala

Distributed systems

Event-driven design

Leadership/mentoring

Tools

Kafka

Spark/Hive/Flink

Airflow/Luigi

Kubernetes (EKS/Helm)

AWS

SQL/NoSQL databases

Job description

Role overview

Lead engineering work on backend identity services that collect, resolve, and maintain large volumes of consumer signals. The systems support identity profiles and platform integrations, so the role combines distributed systems and data engineering with a focus on availability, speed, scale, and transparent data handling. You'll help shape architecture and technical direction while working across engineering, product, and data teams.

Responsibilities

• Design and build APIs and backend services for identity resolution, graph transparency, and integrations.


• Develop and tune event-driven pipelines and workflows that process high volumes of signals.


• Deploy and operate cloud-native services on Kubernetes, using repeatable deployment practices.


• Improve reliability, observability, scalability, and performance across services and data pipelines.


• Work with product, engineering, and data partners to deliver end-to-end identity capabilities.


• Mentor engineers and influence architecture and roadmap decisions.

Requirements

• At least five years in backend or data engineering, including work at scale.


• Strong proficiency in Python, Java, or Scala, with experience in APIs, distributed systems, and event-driven design.


• Hands-on knowledge of Kafka or a comparable event platform, data processing frameworks such as Spark, Hive, or Flink, and workflow schedulers such as Airflow or Luigi.


• Experience with Kubernetes; familiarity with EKS, Helm, or service meshes is relevant.


• Solid SQL, data modeling, and AWS cloud skills.


• Familiarity with columnar or NoSQL databases, plus a record of technical leadership, communication, and mentoring.

Nice to have

Experience with large-scale or multi-tenant systems, real-time streaming, open table formats such as Iceberg, Hudi, or Delta Lake, or security, compliance, and privacy in identity systems.

Benefits and work setup

Benefits include unlimited paid time off, medical, dental, and vision coverage, employee equity, discounts, wellness classes, and pet insurance. The stated annual salary range is $150,000-$200,000, depending on location and experience.