Senior Devops Engineer (Data Platform)

TL;DR

Senior Devops Engineer (Data Platform): Driving data infrastructure strategy and establishing standardized patterns for AI/ML workloads with an accent on architectural decisions across data and engineering teams. Focus on building scalable analytics capabilities and ensuring performance and cost-effectiveness for critical analytics systems.

Location: Tel Aviv, Israel

Company

hirify.global is the leading platform to create and grow games and interactive experiences.

What you will do

• Design and implement scalable data infrastructure across multiple environments using Kubernetes, orchestration platforms, and IaC to power AI, ML, and analytics ecosystem
• Shape the technical vision and roadmap for data infrastructure capabilities, aligning DevOps, Data Engineering, and ML teams around common patterns and practices
• Improve data pipeline deployment, monitoring tools, and self-service capabilities that empower data teams to deliver insights faster with higher reliability
• Build and optimize infrastructure that supports diverse data workloads from real-time streaming to batch processing, ensuring performance and cost-effectiveness for critical analytics systems
• Collaborate with engineering leaders across data teams, champion modern infrastructure practices, and mentor team members to elevate how data systems are built, deployed, and operated at scale

Requirements

• 3+ years of hands-on DevOps experience building, shipping, and operating production systems.
• Coding proficiency in at least one language (e.g., Python or TypeScript); able to build production-grade automation and tools.
• Deep experience with AWS, GCP, or Azure (core services, networking, IAM).
• Strong understanding of Kubernetes as a system (routing/networking, scaling, security, observability, upgrades), with proven experience integrating data-centric components (e.g., Kafka, RDS, BigQuery, Aerospike).
• Design and implement infrastructure automation using tools such as Terraform, Pulumi, or CloudFormation.
• Experience implementing pipelines and advanced delivery using tools such as Argo CD / Argo Rollouts, GitHub Actions, or similar.
• Experience with metrics, logs, and traces; actionable alerting and SLOs using tools such as Prometheus, Grafana, ELK/EFK, OpenTelemetry, or similar.

Nice to have

• Demonstrated success building and optimizing data pipeline deployment using modern tools (Airflow, Prefect, Kubernetes operators) and implementing GitOps practices for data workloads
• Track record of creating and improving self-service platforms, deployment tools, and monitoring solutions that measurably enhance data engineering team productivity
• Extensive experience designing infrastructure for data-intensive workloads including streaming platforms (Kafka, Kinesis), data processing frameworks (Spark, Flink), storage solutions, and comprehensive observability systems

Culture & Benefits

• Committed to fostering an inclusive, innovative environment and celebrate employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation.