Why Verifone
For more than 30 years, Verifone has established a remarkable record of leadership in the electronic payment technology industry. Verifone is one of the leading electronic payment solutions brands and among the largest providers of electronic payment systems worldwide.
Verifone has a diverse, dynamic, and fast-paced work environment in which employees are focused on results and have opportunities to excel. We take pride in working with leading retailers, merchants, banks, and third-party partners to invent and deliver innovative payment solutions around the world. We strive for excellence in our products and services and are obsessed with customer happiness.
Across the globe, Verifone employees are leading the payments industry through experience, innovation, and an ambitious spirit. Whether it’s developing the next generation of secure payment systems or finding new ways to bring electronic payments to emerging markets, the Verifone team is dedicated to the success of our customers, partners, and investors. It is this passion for innovation that drives every Verifone employee toward personal and professional success.
Verifone is proudly an in-office work culture as we see immense benefits to career development and business results from our colleagues being physically co-located.
What’s Exciting About the Role
Verifone is looking for a Data Platform Engineer to join our Platform Engineering team. Rather than being a single-technology specialist position, this is a unique opportunity to your generalist skillset to own and evolve a broad data platform that spans streaming pipelines, multiple database technologies, on prem and cloud infrastructure, and DevOps/SRE operational tooling.
We are looking for experience in core technologies including Kafka, Redis, Data Lake technologies and Cloud Engineering, with the opportunity to leverage other skills such as PostgreSQL, MySQL, MongoDB, SQL Server and more. You will design and operate end-to-end data pipelines that power new AI and analytics initiatives, migrate streaming services to Kubernetes, and build the automation and tooling that reduces operational toil across the team.
If you are energized by working across the full data stack—pipelines, databases, infrastructure, observability, and CI/CD—rather than going deep on a single technology, this role is built for you.
Key Responsibilities
Data Platform & Pipeline Development
- Design, build, and optimize end-to-end data pipelines—streaming and batch—that serve Verifone’s AI, machine learning, and analytics initiatives.
- Work with diverse data technologies and formats: streaming via Kafka, batch via ETL processes, file formats such as Parquet, and table formats such as Iceberg or Delta Lake.
- Collaborate with data engineering and development teams to enforce best practices for data flow, schema design, security, scalability, and performance.
- Continuously improve data pipeline reliability, latency, and throughput across the full SDLC.
- Support and integrate AWS data tooling including Athena, Glue, Redshift, and S3-based data lake patterns.
Streaming Infrastructure (Kafka & Ecosystem)
- Manage and support Apache Kafka clusters (including AWS MSK), Kafka Connect, and KSQL for high-throughput, fault-tolerant event streaming.
- Handle day-to-day Kafka operations: offset management, lag monitoring, consumer group management, cluster rebalancing, and partition tuning.
- Perform cluster maintenance: upgrades, configuration changes, scaling events, and health checks.
- Drive incident response and root cause analysis (RCA) for streaming platform issues.
- Participate in the active effort to migrate Kafka and related services to Kubernetes.
Database Operations
- Operate and support multiple database technologies in production: Redis, PostgreSQL and MySQL (indexing, replication, HA/DR, query tuning), and MongoDB.
- Perform routine maintenance across database platforms: upgrades, configuration tuning, health monitoring, and capacity planning.
- Support Snowflake data warehouse operations and integrations as part of the broader analytics stack.
- Implement and uphold data security practices including encryption-in-transit/at-rest, secrets management, and least-privilege access across all data stores.
DevOps, SRE & Automation
- Develop and maintain automation scripts (Python, Bash) to reduce manual toil and improve platform reliability.
- Design, implement, and manage CI/CD pipelines for patching, deployment, and configuration automation.
- Build and maintain Infrastructure as Code (IaC) using Terraform, Ansible, or similar tools.
- Containerize and orchestrate workloads using Docker and Kubernetes.
- Manage cloud infrastructure on AWS: EC2, VPC, IAM, MSK, ElastiCache, CloudWatch, and related services.
- Set up and maintain observability tooling—metrics, logs, and tracing—and participate in on-call incident response.
- Support cloud migration tasks, moving workloads between on-prem and cloud environments.
What We Offer
- Broad platform ownership—you will work across Kafka, Redis, MongoDB, PostgreSQL, MySQL, Snowflake, and more, growing as a well-rounded platform engineer rather than a single-tool specialist.
- Direct impact on Verifone’s global payment infrastructure—your work keeps billions of transactions flowing reliably every year.
- Ground-floor involvement in building the data pipelines that will drive Verifone’s AI, machine learning, and analytics strategy.
- Hands-on participation in a Kafka-to-Kubernetes migration—a meaningful infrastructure modernization project from day one.
- Mentorship from senior engineers and platform architects with deep production experience.
- Clear career progression path from mid-level to senior and lead engineer.
- Funded certification paths—Confluent (CCDAK, Certified Administrator), AWS (Solutions Architect, MSK Specialty), CKA, dbt—plus budget for courses and technical conferences.
- Hybrid/remote working flexibility with a collaborative team culture.
- Competitive compensation with performance-based incentives.
Required Qualifications / Skills
We are looking for a well-rounded platform engineer with experience in Kafka, Redis, Data Lake technologies and Cloud Engineering. Candidates should demonstrate breadth across data, databases, DevOps and SRE skills:
- 4+ years of overall engineering experience, with demonstrated work across data pipelines, database operations, and infrastructure—not limited to a single technology.
- Hands-on experience with Kafka or another distributed streaming platform (Kafka, Kinesis, Pulsar) in a production environment.
- Operational experience with at least two of the following database technologies: Redis, PostgreSQL, MySQL, MongoDB, Redshift or Snowflake.
- Proven data pipeline experience: building or maintaining ETL/ELT processes, batch jobs, or streaming pipelines that serve analytics or operational use cases.
- Strong scripting and automation skills (Python and/or Bash) with a track record of reducing manual toil.
- CI/CD pipeline development and Infrastructure-as-Code experience (Terraform preferred).
- Solid Linux fundamentals: networking basics, log analysis, system troubleshooting, process/memory/disk management.
- Cloud engineering experience, preferably AWS (EC2, VPC, IAM, MSK/ElastiCache, CloudWatch).
- Familiarity with observability practices—metrics, logs, tracing—and incident response workflows.
- Understanding of distributed systems trade-offs: availability, consistency, partitions, backpressure.
- Strong communication skills including the ability to present platform status and technical decisions to non-technical stakeholders.
- Flexibility for on-call rotation and occasional weekend support.
Preferred Skills (Highly Desired)
Data Engineering Depth
- Experience with stream processing frameworks: Kafka Streams, Apache Flink, or similar.
- Familiarity with data lake table formats: Apache Iceberg, Delta Lake, or Apache Hudi.
- Hands-on experience with AWS data services: Athena, Glue, Redshift, or Lake Formation.
- Working knowledge of Snowflake—data loading, query optimization, or integration patterns.
- Understanding of data quality, data lineage, or schema registry concepts.
Infrastructure & Security
- Container/Kubernetes depth: deployments, StatefulSets, storage classes, Helm.
- On-prem infrastructure experience: VMware/KVM, SAN/NAS storage, network configuration.
- Security and compliance experience, particularly PCI-DSS (Payment Card Industry Data Security Standard).
- Secrets management tooling: HashiCorp Vault, AWS Secrets Manager, or similar.
