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Data Engineer
2 weeks ago
Responsibilities
- Data Pipeline Development: Design, build, and maintain scalable, efficient data pipelines in Python.
- AWS Ecosystem: Leverage services like S3 and EC2 for data storage, retrieval, and processing in production environments.
- Big Data Handling: Develop and optimize systems to handle petabyte-scale datasets with a focus on performance, reliability, and cost-effectiveness.
- Monitoring & Reliability: Implement robust monitoring, alerting, and logging to ensure smooth data flow and quickly troubleshoot issues.
- Collaboration: Work cross-functionally with data scientists, software engineers, and product teams to understand data needs and deliver optimized solutions.
- Video Processing (Preferred): If applicable, process and manage video data for analytics, quality control, and other use cases.
- Python Proficiency: Strong coding skills in Python (including familiarity with libraries for data manipulation and analysis).
- AWS Expertise: Hands-on experience using core AWS services (S3, EC2, possibly Lambda, EMR, or ECS).
- Big Data Skills: Demonstrated ability to work with large-scale datasets (petabyte-level), ensuring high performance and scalability.
- Database & Storage: Familiarity with SQL and NoSQL databases, plus data lakes and distributed data storage practices.
- Automation & Scripting: Comfortable building CI/CD pipelines and automating repetitive tasks.
- Video Processing: Experience handling or transforming video data (e.g., transcoding, extracting metadata).
- Machine Learning Pipelines: Familiarity with ML workflows or frameworks (TensorFlow, PyTorch, etc.).
- Orchestration Tools: Knowledge of Airflow, Luigi, or other workflow orchestration frameworks.
- Security Best Practices: Understanding of AWS IAM, encryption, and compliance standards.
- An opportunity to work with massive data sets and cutting-edge technologies in the cloud.
- A collaborative environment with a talented, diverse team of engineers and data experts.
- Competitive compensation and benefits with room for career growth and professional development.
- A chance to influence and shape high-performance data-driven applications.
