[Hiring] DataOps Platform Engineer @Paramo Technologies

Role Description

We are looking for a DataOps Platform Engineer to help operate, automate, and evolve our data platform. You will work across distributed systems, observability, infrastructure-as-code, and hybrid environments (on-prem + Azure), ensuring stability, scalability, and reliability for teams building on top of the platform.

This role focuses on platform enablement — not building data pipelines — and requires strong engineering fundamentals, an automation mindset, and experience with modern data-infrastructure tooling.

• Operate and maintain core platform services: Spark, Flink, Airflow, OpenMetadata, and supporting components.
• Support and optimize internal analytical engines such as StarRocks, and assist in the rollout of technologies like Neo4j.
• Operate hybrid infrastructure: on-prem (VMware vSphere) + Azure (networking, identity, managed services, private connectivity patterns).
• Enable platform connectivity and operational readiness for data warehouse / analytics ecosystems (e.g., Synapse, Snowflake, BigQuery or similar): authentication/access patterns, runtime integration, operational monitoring (no pipeline ownership).
• Implement and maintain Infrastructure as Code using Terraform.
• Automate configuration and deployments using Ansible.
• Maintain GitOps workflows using ArgoCD.
• Manage CI/CD pipelines for platform components via Jenkins.
• Maintain and improve the observability stack: Logging: Fluent Bit + Graylog; Metrics/alerts/dashboards: New Relic / Grafana.
• Support Splunk usage including platform-side onboarding and operational administration tasks (e.g., forwarders/integrations, source onboarding, access/retention patterns as needed in coordination with security/IT).
• Drive platform reliability through incident response, RCA, and lifecycle operations (upgrades, patches, feature enablement), working in an Agile/Kanban delivery model.
• Produce and maintain high-quality documentation: runbooks, operational guides, onboarding docs, and service ownership standards.

Qualifications

• Strong experience (+5 years) operating distributed systems or data platform components (Spark/Flink/Airflow).
• Practical experience operating cloud/hybrid environments, including Azure services used in data platforms (networking/connectivity, identity, managed services).
• Solid Linux, networking, troubleshooting, and automation skills.
• Hands-on experience with Terraform and Ansible.
• Practical experience with GitOps (ideally ArgoCD).
• Experience with CI/CD (preferably Jenkins).
• Hands-on familiarity with observability fundamentals: logs, metrics, alerts (Fluent Bit, Graylog, New Relic, Grafana).
• Strong operational ownership: incident handling, problem management, and continuous improvement (SLIs/SLOs, alert quality, capacity).
• Upper-intermediate English.
• On-Call availability.

Requirements

• Experience with analytical databases / distributed engines (StarRocks, ClickHouse, Druid, etc.) is a bonus.
• Interest or exposure to graph databases (Neo4j) is a bonus.
• Familiarity with developer-platform enablement tools such as Backstage (or similar) is a bonus.
• Exposure to Azure ML Studio or adjacent ML platform tooling (enablement/ops perspective) is a bonus.

Benefits

• 22 days of annual leave.
• 10 days of public/national holidays.
• Health insurance options.
• Access to online learning platforms.
• On-site English classes in some countries, and more.