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Data Engineer
Job summary
A leading e-commerce company is seeking a Data Engineer to develop data pipelines and contribute to their innovative projects in fashion and home décor. This 100% remote role requires proficiency in PySpark, Databricks, and Terraform. The ideal candidate will have strong problem-solving and communication skills, ensuring effective collaboration with the team. Join them to leverage your expertise in a fast-paced and evolving environment.
Qualifications
- Proficiency in PySpark and Spark SQL for data processing.
- At least 1 year of experience with Terraform and GitOps practices.
- Strong understanding of ETL processes and data warehousing.
Responsibilities
- Design and deploy efficient data pipelines as per project requirements.
- Analyze business challenges and collaborate with project team.
- Document processes thoroughly and conduct peer reviews.
Skills
Tools
Industry: E-commerce (Fashion & Home)
Location: Portugal
Work Model: 100% Remote
Start Date: ASAP
Project Language: English
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.
- 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.
- 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.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.