Data Platform Engineer

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.

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:

5+ 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.

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.

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.

Verifone is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. Verifone is also committed to compliance with all fair employment practices regarding citizenship and immigration status.