Lead DevOps & Data Platform Consultant

EPAM Systems

Turkey

On-site

TRY 900,000 - 1,300,000

Full time

4 days ago
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Benefits offered by this job

Extra leave days
Referral bonuses
Private health insurance
Well-being events

Job summary

EPAM Systems is seeking a driven Lead DevOps/Consultant to assess client infrastructure for Enterprise Data Platform deployment. You will identify gaps, document remediation actions, and coordinate with data engineering and DevOps teams to align deployment strategies.

The role involves creating automation scripts and collaborating with vendors to ensure compatibility and support. You will deploy workloads on Kubernetes, monitor performance, and contribute to continuous improvement of deployment

Qualifications

  • 5+ years in DevOps or Site Reliability Engineering.
  • Experience assessing infrastructure for data platform deployments.
  • Ability to analyze complex client environments and identify integration challenges.
  • Experience collaborating across cross-functional teams and with external vendors.

Responsibilities

  • Conduct infrastructure assessments for EDP rollout feasibility.
  • Identify gaps and remediation actions.
  • Collaborate with data engineering and DevOps teams to align deployment strategies.
  • Develop and maintain deployment automation scripts and tools.
  • Coordinate with third-party vendors to ensure compatibility and support.
  • Monitor infrastructure performance and provide feedback for optimization.
  • Deploy platform workloads on Kubernetes.

Skills

DevOps
SRE
Docker
Kubernetes
CI/CD
Argo
Python
Linux
English B2

Tools

Airflow
MLflow

Job description

EPAM Systems is seeking a driven Lead DevOps/Consultant to assess client infrastructure for Enterprise Data Platform deployment. You will identify gaps, document remediation actions, and coordinate with data engineering and DevOps teams to align deployment strategies.

The role involves creating automation scripts and collaborating with vendors to ensure compatibility and support. You will deploy workloads on Kubernetes, monitor performance, and contribute to continuous improvement of deployment

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