DevOps Engineer

22 hours ago

Islamabad, Islamabad, Pakistan NETS-International Group Full time 60,000 - 120,000 per year

About the Role:

We are looking for a passionate
DevOps Engineer
with 1–3 years of experience to join our Data & AI Operations team. The ideal candidate will have hands-on experience managing data warehouse operations, debugging ETL and orchestration workflows, and deploying machine learning models in production. This role focuses on building scalable MLOps frameworks and automated CI/CD pipelines to support our growing data and AI initiatives.

Key Responsibilities:

  • Manage and optimize
    data warehouse operations
    , ensuring high availability and performance.
  • Debug and maintain Informatica, SLJM, and Apache Airflow
    jobs and workflows.
  • Deploy, monitor, and operationalize ML models
    , including retraining and performance evaluation.
  • Design and develop scalable MLOps frameworks
    for model deployment, tracking, and governance.
  • Build and maintain
    CI/CD pipelines
    to automate data and model workflows using
    Docker
    and
    Kubernetes
    .
  • Collaborate with data scientists, data engineers, and software developers to ensure smooth integration and delivery of AI/ML solutions.
  • Continuously improve automation, monitoring, and alerting across DevOps and MLOps environments.

Required Qualifications:

  • Education:
    Bachelor's degree in Computer Science, Software Engineering, Data Engineering, or a related field.
  • Experience:
    1–3 years of experience in DevOps, DataOps, or MLOps roles.
  • Technical Skills:
  • Strong understanding of
    data warehouse operations
    .
  • Hands-on experience with
    Informatica
    ,
    SLJM
    , and
    Apache Airflow
    .
  • Practical knowledge of
    ML model deployment and monitoring
    .
  • Proficiency in
    containerization and orchestration tools
    —
    Docker
    and
    Kubernetes
    .
  • Familiarity with
    CI/CD pipelines
    and version control (Git, Jenkins, etc.).
  • Good scripting and automation skills (Python, Bash, etc.).

Preferred Qualifications:

  • Exposure to
    cloud platforms
    (AWS, Azure, or GCP).
  • Knowledge of
    MLOps tools
    (MLflow, Kubeflow, Airflow DAGs for ML pipelines).
  • Relevant certifications such as
    AWS DevOps Engineer
    or
    Azure DevOps Engineer
    .

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