DevOps Engineer – Big Data

Naviteq Ltd; United States; Remote; USD 130,000 - 190,000; Full time

Benefits offered by this job

Fully remote work

Flexible, distributed team

Ownership over architecture

Job summary

Naviteq Ltd is seeking a DevOps Engineer with hands-on Big Data experience to design, deploy and scale cloud infrastructure on AWS. You’ll manage Terraform IaC, EKS-based workloads, and production data platforms with Hadoop, Kafka, ClickHouse, Redis or Elasticsearch.

You will build robust CI/CD pipelines, set up monitoring, and drive optimization across large-scale data systems, collaborating with data and backend teams.

Qualifications

• 5+ years of hands-on DevOps/Infrastructure/SRE experience.
• Strong AWS experience and Terraform proficiency.
• Production Kubernetes(EKS) exposure and big data platform ops.
• Experience deploying and tuning Hadoop, Kafka, ClickHouse, Redis or Elasticsearch.
• Familiarity with CI/CD pipelines and automation tooling.
• Proficient in Python, Bash or Go scripting.
• Knowledge of monitoring/observability tools and Linux fundamentals.
• Strong English communication and independent, proactive work style.

Responsibilities

• Design, build and maintain AWS cloud infrastructure with Terraform.
• Deploy containerised workloads on Kubernetes (EKS) and scale.
• Configure and operate large-scale data platforms (Hadoop, Kafka, etc).
• Ensure HA, performance and data reliability of clusters.
• Build and improve CI/CD pipelines and automation.
• Set up monitoring, alerting and logging; drive RCAs.
• Plan capacity, upgrades and cost optimization for data infra.
• Collaborate with data and backend teams to support platforms.

Skills

DevOps

AWS

Terraform

Kubernetes

Big Data

Hadoop

Kafka

Elasticsearch

Redis

ClickHouse

CI/CD

Python

Bash

Go

Prometheus

Grafana

ELK

Datadog

Linux

English

Tools

Jenkins

GitHub Actions

GitLab CI

ArgoCD

Job description

A global adtech company with 1,200 employees and offices in the US, Israel, Europe and APAC. It runs an end-to-end advertising platform (DSP + SSP) for leading global brands. Its systems process millions to billions of events per second, so reliable, scalable data infrastructure is core to the business.

The Role

We're looking for a DevOps Engineer with hands-on Big Data experience to build, run and scale the cloud infrastructure behind our high-throughput data platforms. You'll combine classic DevOps work on AWS, Terraform and EKS with configuring, tuning and operating large-scale data systems in production.

Responsibilities

• Design, build and maintain cloud infrastructure on AWS using Terraform (IaC)
• Deploy and operate containerised workloads on Kubernetes (EKS)
• Configure, manage, scale and tune Big Data platforms such as Hadoop, Kafka, ClickHouse, Redis or Elasticsearch
• Ensure high availability, performance and data reliability of clusters handling very large data volumes
• Build and improve CI/CD pipelines and automation
• Set up monitoring, alerting and logging; troubleshoot production incidents and drive root-cause analysis
• Plan capacity, upgrades and cost optimization of the data infrastructure
• Work closely with data and backend engineering teams to support their platforms

Requirements

• 5+ years as a DevOps / Infrastructure / SRE engineer
• Strong hands-on experience with AWS (must)
• Strong experience with Terraform (must)
• Production experience with Kubernetes, preferably EKS (must)
• Hands-on experience configuring and managing at least one Big Data platform in production: Hadoop, Kafka, ClickHouse, Redis or Elasticsearch (must)
• CI/CD tools (Jenkins, GitHub Actions, GitLab CI, ArgoCD)
• Scripting in Python, Bash or Go
• Monitoring and observability tools (Prometheus, Grafana, ELK, Datadog)
• Solid Linux and networking fundamentals
• Strong English; communicative, independent, proactive team player

What we offer:

• A great team of experienced engineers who value collaboration and knowledge sharing
• A large-scale global project used by the world's best-known brands
• Fully remote work with a flexible, distributed team
• Real ownership and influence over architecture and technical decisions