Lead Platform Engineer - Kafka and Streaming Data

Job Description

Lead Platform Engineer, Kafka and Streaming Data

Ready to take your career global?

Make your mark at one of the biggest names in payments.

We're looking for a Lead Platform Engineer to join our Enterprise Data Platform Engineering team as the hands-on technical lead for our new streaming data platform. We are building a shared platform on Apache Kafka for the whole company. It carries payment events in real time to applications, to the data lake and to services that need the current state of that data with low latency. You will shape the technical direction of the platform and own its technical strategy, and you will build it yourself. You will design and write code every week: Terraform, pipelines, stream processing applications and platform services. The team is small, and everyone builds. In your first year you will help stand up the platform in production, onboard the first teams and start moving existing Kafka workloads onto it. You will share the platform on-call rotation.

What you'll own

• The platform, designed and built in code: Kafka across regions, schema registry and data contracts, connectors and change data capture, stream processing, delivery into Apache Iceberg tables, and real-time serving to applications.

• Self-service for product teams, built as platform services: topic as a service, schema as a service and self-service ingestion of new data sources, with templates for the patterns teams are allowed to use.

• The technical strategy: architecture, standards, roadmap and the plan to move existing Kafka workloads onto the platform. You write the designs and standards the team builds to.

• Card-data protection to PCI DSS. You design and build the streaming encryption module: a stream processing application on Kafka that encrypts or tokenizes card fields in flight through the company's tokenization service. You also own keys, access control and audit evidence.

• Reliability: replication between regions, failover drills, service objectives, monitoring and alerting, load testing, capacity planning, and the root cause of production incidents.

• The move onto the platform: live workloads moved without downtime with the teams that own them, existing self-managed Kafka kept healthy until it retires, and the platform's cost shown to each team that uses it.

What you'll bring

• Expert, hands-on Apache Kafka. You have designed and run a multi-region Kafka platform used by many teams and moved live workloads onto it without downtime. You know replication between clusters, Kafka Connect, change data capture and schema registry in depth.

• Kafka on Kubernetes. You have built and run self-managed Kafka on Kubernetes entirely through automation and infrastructure as code, including operators, upgrades, scaling and recovery.

• Strong programming skills with deep Kafka knowledge. You write production code in Java with the Kafka clients, Kafka Streams or Apache Flink. You can design and build platform functionality such as an encryption module: an application that transforms every event in flight by calling an external service, without losing data or falling behind.

• Strong cloud engineering on AWS or Google Cloud, across regions. You know networking and private connectivity, identity and access, encryption, and key and secrets management.

• Infrastructure as code as a daily practice. You write, review and test Terraform modules, build and rebuild environments from code, put guardrails and policy in code, and turn approved patterns into reusable templates.

• DevOps and automation. You have built CI/CD pipelines and self-service platform services, such as topic and schema provisioning and data ingestion, and you prove service objectives with monitoring, load tests and failover tests.

• Technical direction. You have shaped the direction and strategy of a shared platform, written the designs and standards others build to, worked with vendors, and led engineers while building alongside them.

It's a bonus if you have

• Experience in payments, fintech or another highly regulated industry, especially with PCI DSS.

• Certifications: Confluent Certified Administrator for Apache Kafka or Confluent Certified Developer for Apache Kafka, and AWS or Google Cloud certifications.

• Contributions to open-source Apache Kafka or related projects.

• Experience with a managed Kafka service, Apache Iceberg, low-latency data serving or distributed NoSQL databases, or work on more than one public cloud.

EEOC Statement

Global Payments is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, genetic information, national origin, disability, veteran status, and other protected characteristics. The EEO is the Law poster is available here.

If you are made a conditional offer of employment and will be working in the United States, you will be required to undergo a drug test. In developing this job description care was taken to include all competencies and requirements needed to successfully perform the position. Reasonable accommodations will be provided for individuals with qualified disabilities both during the hiring process, as well as to allow the individual to perform the essential functions of the job, if hired.

Washington Candidates: Click here for information on the Fair Chance Act.