Digitalization Engineer

Role Overview:

Data Science Engineer

Key Responsibilities:

• Data Engineering & Integration:

  • Design and implement data pipelines using

    Azure Data Factory

    ,

    Azure Synapse Analytics

    , and

    Azure Databricks

    .
  • Integrate structured and unstructured data from multiple sources into Azure-based data lakes and warehouses.

• Machine Learning & AI Development:

  • Build and deploy ML models using

    Azure Machine Learning

    and

    Python/R

    .
  • Optimize model performance and manage lifecycle with

    MLOps

    practices.

• Cloud Architecture & Optimization:

  • Architect scalable solutions using

    Azure Storage

    ,

    Azure SQL Database

    , and

    Azure Kubernetes Service (AKS)

    .
  • Ensure cost optimization and performance tuning across Azure resources.

• Security & Compliance:

  • Implement data governance, security policies, and compliance standards (GDPR, HIPAA, etc.).
  • Manage role-based access and encryption for sensitive data.

• Collaboration & Documentation:

  • Work closely with data scientists, analysts, and business stakeholders to deliver actionable insights.
  • Document workflows, architecture diagrams, and best practices.

Required Skills & Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, or related field.
• 3+ years of experience in

  Azure Data Services

  and

  Cloud-based Data Engineering

  .
• Hands-on experience with

  Azure Machine Learning

  ,

  Data Factory

  ,

  Synapse

  , and

  Databricks

  ,

  AWS

• Strong understanding of

  ETL processes

  ,

  data modeling

  , and

  big data frameworks

• Excellent problem-solving and communication skills.