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emagine logo

Data Engineer

emagine
Posted 1 hour ago
🌍Belgium, Poland, Portugal🏠Remote📁Data & Analytics
Is this job info correct?
Industry: E-commerce (Fashion & Home)

Location: Portugal

Work Model: 100% Remote

Start Date: ASAP

Project Language: English

Project Overview:

Join a leading e-commerce company in fashion and home décor, as they undertake critical data engineering projects to support their evolving business needs. This is an exciting opportunity to contribute to high-impact data solutions for an innovative, customer-focused brand, leveraging the latest in data engineering best practices.

Responsibilities:

  • Project Understanding and Communication:
    • Analyze business and technical challenges from a user perspective.
    • Collaborate with Data Architects and Project Managers to ensure solutions align with the client´s data architecture.
  • Data Pipeline Development:
    • Design, build, and deploy efficient data pipelines according to project requirements.
    • Apply best practices for performance, scalability, and maintainability.
    • Use Terraform to deploy and manage infrastructure efficiently.
  • Testing and Deployment:
    • Define test cases and conduct testing in collaboration with the Project Manager.
    • Present completed developments to Data Architects and Lead DataOps, ensuring smooth deployment and active monitoring post-deployment.
  • Documentation and Peer Review:
    • Document processes, tests, and results thoroughly.
    • Conduct peer reviews and participate in code reviews for quality assurance.
Requirements:

Hard Skills:

  • Proficiency in PySpark and Spark SQL for data processing.
  • Experience with Databricks and Delta Live Tables for ETL and workflow orchestration.
  • Familiarity with Azure Data Lake Storage for data storage and management.
  • At least 1 year of experience with Terraform and GitOps practices for infrastructure deployment.
  • Strong understanding of ETL/ELT processes, data warehousing, data lakes, and data modeling.
  • Knowledge of orchestration tools (e.g., Apache Airflow) for pipeline scheduling and management.
  • Experience with data partitioning and lifecycle management in cloud storage.

Optional: Experience with Databricks Asset Bundles, Kubernetes, Apache Kafka, and Vault is a plus.

Soft Skills:

  • English Fluency: Strong written and verbal English skills in a working environment.
  • Communication: Ability to convey technical concepts effectively and understand user needs.
  • Organizational Skills: Detail-oriented with the ability to maintain structured documentation.
  • Problem-Solving: Proactive approach to understanding and addressing data challenges.

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