DataOps Engineer

TL;DR

DataOps Engineer: Designing, deploying, and operating Kubernetes-based infrastructure for a large-scale data processing platform with an accent on reliability, performance, and cost-efficiency. Focus on tuning Spark-on-K8s, managing Airflow infrastructure, and building robust CI/CD and observability tooling.

Location: Global remote workforce. Company based in Ramat Gan, Israel.

Company

hirify.global is a location analytics platform providing unprecedented visibility into locations, markets, and consumer behavior, having achieved unicorn status and rapid growth.

What you will do

• Design, deploy, and operate Kubernetes-based infrastructure for Apache Spark and large-scale data processing workloads.
• Ensure reliability, performance, and cost-efficiency of the data platform, including SLAs, autoscaling, and resource quotas.
• Manage Spark-on-K8s configurations, Airflow infrastructure, and Databricks integration, tuning for throughput and latency.
• Build and maintain CI/CD pipelines and infrastructure-as-code for data platform components.
• Develop observability tooling, including metrics, logging, and alerting, for proactive issue surfacing.
• Collaborate with Data Engineers to translate workload patterns into infrastructure decisions.

Requirements

• 5+ years of experience in a production infrastructure, SRE, or DevOps role.
• 2+ years of hands-on experience running Apache Spark, Flink, or similar data processing workloads in production.
• Strong Kubernetes experience, including Spark-on-K8s, autoscaling, and resource management.
• 2+ years with infrastructure-as-code tools (Terraform, Pulumi, or similar).
• Proficiency in at least one general-purpose language, preferably Python or Go.
• Experience with workflow orchestration tools, particularly Apache Airflow.
• Solid understanding of cloud infrastructure, preferably GCP (GCS, GKE, IAM).
• Strong observability skills: metrics pipelines, structured logging, and alerting frameworks.

Nice to have

• Familiarity with Delta Lake, Parquet, and columnar storage formats.
• Experience with data quality frameworks and pipeline lineage tooling.
• Knowledge of query optimization, partition strategies, and Spark performance tuning.
• Experience managing queues and databases (Kafka, PostgreSQL, Redis, or similar).

Culture & Benefits

• Join a rapidly growing company pioneering a new market.
• Take a central and critical role at hirify.global.
• Work with and learn from top-notch talent.
• Competitive salary and excellent benefits.
• Committed to maintaining a drug-free workplace and promoting a safe, healthy environment.
• Equal opportunity employer with a global remote workforce.