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21 hours ago
This role involves leading the full lifecycle of designing and building scalable, high-performance data pipelines across diverse platforms and data sources.
The successful candidate will be responsible for enhancing data infrastructure to ensure optimal performance, reliability, and scalability.
A key aspect of this role is performing detailed code reviews and offering feedback to uphold best practices and high coding standards.
The chosen applicant will also support the development of other data engineers through mentoring and technical guidance.
Collaboration with cross-functional teams is essential to gather data needs and deliver effective engineering solutions.
The ideal candidate will have expertise in resolving complex data challenges, ensuring data integrity, availability, and consistency.
RequirementsA Bachelor's or Master's degree in Computer Science, Engineering, or a related field is required.
No less than 5 years of hands-on experience in data engineering or backend data systems development is necessary.
- Experience in building data solutions at enterprise scale is desirable.
- Data Pipeline Orchestration and Workflow Management skills are essential.
- Familiarity with Apache Airflow, Prefect, Apache NiFi, Talend, AWS Glue, Azure Data Factory, and DataDog or similar tools for tracking and monitoring data pipelines is required.
- DevOps and CI/CD Tools such as Docker, Git, CircleCI (or other CI/CD pipelines) for containerization, version control, and automated deployments are also necessary.
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