Associate Staff Engineer - DataOps

Nagarro; Rio de Janeiro; Híbrido; BRL 180 000 - 300 000; Tempo integral

Resumo da oferta

Nagarro Brazil is seeking a Senior DataOps/DevOps Engineer for a hybrid role bridging data operations, DevOps, and infrastructure support to keep data-driven systems reliable and optimized.

The role involves end-to-end ops, incident management, monitoring with Datadog, Grafana, Prometheus, and collaboration with global teams to scale deployments and ensure performance across analytics platforms.

Qualificações

• 6 to 8+ years in DataOps, DevOps, infrastructure operations, site reliability engineering or analytics platform support.
• Intermediate SQL for data extraction, transformation, and diagnostics.
• CI/CD pipelines knowledge (Jenkins, Azure DevOps, Git).
• Monitoring/observability tools (Datadog, Grafana, Prometheus).
• Scripting in Python or Shell for automation and diagnostics.
• Containerization (Docker, Kubernetes) and cloud platforms AWS/Azure/GCP; AWS knowledge required.
• Infrastructure-as-code (Terraform, Ansible).
• Operational Excellence: incident management and SLA/SLI/SLOs.
• Analytical mindset and strong cross-functional collaboration.
• Agility: comfortable working in fast-paced environments.

Responsabilidades

• Manage end-to-end data and infrastructure operations, from writing SQL queries to CI/CD pipeline creation and optimization and VM and cloud-based deployments.
• Drive incident and request management through ServiceNow, ensuring SLA compliance, ownership, and proactive issue resolution.
• Implement and refine monitoring and observability frameworks using Datadog; Grafana; Prometheus to maintain uptime, identify bottlenecks, and enhance system reliability.
• Collaborate across global teams including Data Engineering, Product, and IT Infrastructure to resolve production issues, improve deployment practices, and optimize system performance.
• Conduct root cause analyses and contribute to blameless post-incident reviews and preventive action plans.
• Collaborate with security and compliance teams to uphold operational standards and data protection practices.
• Contribute to automation and continuous improvement initiatives through scripting (Python, Shell) and infrastructure-as-code (Terraform, Ansible) principles
• Support the data lifecycle, ensuring accuracy, integrity, and accessibility of data pipelines and dashboards across analytics platforms.
• Collaborate with Data Engineering teams to ensure data pipelines, ETL processes, and analytics platforms are performant, reliable, and production-ready.
• Collaborate on capacity planning, scaling, and performance optimization to ensure reliability during growth and high-load scenarios.
• Use operational metrics (MTTR, uptime, failure rate, latency) to drive service reliability improvements
• Participate in Agile ceremonies within a Scrum/Kanban model, aligning with delivery squads to ensure cross-functional visibility and operational excellence.
• Operate within a 24-5 rotational model, supporting mission-critical environments and ensuring business continuity across time zones.

Conhecimentos

DataOps

DevOps

SQL

CI/CD

Python

Shell

Observability

Collaboration

Agility

Ferramentas

Docker

Kubernetes

AWS

Azure

GCP

Terraform

Ansible

Jenkins

Azure DevOps

Git

Datadog

Grafana

Prometheus

ServiceNow

Descrição da oferta de emprego

We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (15000+ experts across 26 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!

Job Description

This hybrid role bridges Data Operations, DevOps, and Infrastructure Support, ensuring data-driven systems remain reliable, performant, and continuously optimized.

Responsibilities:

• Manage end-to-end data and infrastructure operations, from writing SQL queries to CI/CD pipeline creation and optimization and VM and cloud-based deployments.
• Drive incident and request management through ServiceNow, ensuring SLA compliance, ownership, and proactive issue resolution.
• Implement and refine monitoring and observability frameworks using Datadog; Grafana; Prometheus to maintain uptime, identify bottlenecks, and enhance system reliability.
• Collaborate across global teams including Data Engineering, Product, and IT Infrastructure to resolve production issues, improve deployment practices, and optimize system performance.
• Conduct root cause analyses and contribute to blameless post-incident reviews and preventive action plans.
• Collaborate with security and compliance teams to uphold operational standards and data protection practices.
• Contribute to automation and continuous improvement initiatives through scripting (Python, Shell) and infrastructure-as-code (Terraform, Ansible) principles
• Support the data lifecycle, ensuring accuracy, integrity, and accessibility of data pipelines and dashboards across analytics platforms.
• Collaborate with Data Engineering teams to ensure data pipelines, ETL processes, and analytics platforms are performant, reliable, and production-ready.
• Collaborate on capacity planning, scaling, and performance optimization to ensure reliability during growth and high-load scenarios.
• Use operational metrics (MTTR, uptime, failure rate, latency) to drive service reliability improvements
• Participate in Agile ceremonies within a Scrum/Kanban model, aligning with delivery squads to ensure cross-functional visibility and operational excellence.
• Operate within a 24-5 rotational model, supporting mission-critical environments and ensuring business continuity across time zones.

What You Will Bring Experience:

• 6 to 8+ years in DataOps, DevOps, infrastructure operations, site reliability engineering or analytics platform support
• Technical Expertise:
  • Intermediate SQL for data extraction, transformation, and diagnostics
  • Strong understanding of CI/CD pipelines (Jenkins, Azure DevOps, Git-based version control)
  • Proficiency in monitoring and observability tools (Datadog, Grafana, Prometheus)
  • Hands‑on with Python or Shell scripting for automation and diagnostics
  • Familiarity with containerization (Docker, Kubernetes) and cloud platforms (AWS, Azure, GCP). Knowledge of AWS services is a must
  • Solid grasp of infrastructure‑as‑code concepts (Terraform, Ansible)
• Operational Excellence: Proven record in incident management, maintaining SLA/SLI/SLO s for critical systems and escalation handling in enterprise environments
• Analytical Mindset: Ability to interpret system and data metrics, identify trends, and recommend performance improvements
• Collaboration: Strong communication skills with cross‑functional, global teams across technical and non-technical domains
• Agility: Comfort working in dynamic, fast‑paced environments, maintaining composure and prioritization under pressure

Qualifications

Must have Skills: SQL (Strong), DevOps - AWS (Strong), Python (Strong), CI/CD pipelines