Sr Data Engineer

Company Overview:
Quibble is a leading revenue management company that is revolutionizing the way we use machine learning to drive business growth. We are seeking a highly skilled and motivated ML Ops Engineer to join our team and play a crucial role in deploying and managing our machine learning models at scale.

Job Responsibilities:
- Design, build, and optimize data pipelines using AWS Glue to extract, transform, and load data from various sources into our data lake and data warehouse.
-Work closely with data scientists and analysts to understand their requirements and translate them into efficient data processing workflows.
-Develop and maintain data processing applications using data frames (e.g., Pandas, Spark DataFrame) to perform complex transformations and aggregations.
-Implement best practices for data governance, data quality, and metadata management to ensure the reliability and accuracy of our data.
-Collaborate with cross-functional teams to integrate machine learning models into production systems and automate model deployment using ML Ops tools and frameworks.
-Monitor performance metrics, troubleshoot issues, and optimize the performance of data pipelines and machine learning workflows.

Qualifications:
- Strong background in machine learning principles and algorithms.
- Experience with ML tools and frameworks such as TensorFlow, PyTorch, or scikit-learn.
- Proficiency in query optimization.
- Solid understanding of cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
- Familiarity with DevOps principles and practices.
- Excellent problem-solving and communication skills.
- Ability to work independently and collaborate effectively in a team-oriented environment.

Benefits:
- Competitive compensation.
- Opportunity to work with cutting-edge technologies.
- Career growth and development opportunities.