Data Engineer (Welcome Fresh Graduate)

【Key Attributes】

• Eagerness to learn from senior engineers and follow structured workflows in data engineering and ML projects.
• Ability to handle entry-level tasks (e.g., pipeline maintenance, basic ETL jobs, data preprocessing for ML) while progressively taking on model development challenges.

• Comfort working in a collaborative environment with regular feedback and oversight.

【Job Duties】  

• Assist in designing and maintaining cloud-based data pipelines under supervision, ensuring efficient data extraction, transformation, and loading (ETL) processes.
• Support optimization of data discovery and analytical performance on big data platforms, following predefined transformation logic and data models.
• Collaborate with senior engineers to preprocess data for machine learning workflows, including cleaning, normalization, and feature engineering.
• Apply foundational machine learning techniques (e.g., regression, classification) to build basic predictive models under guidance, contributing to data-driven insights.
• Assist in deploying and monitoring ML models in production environments, ensuring alignment with business goals.
• Collaborate with data analysts and scientists to visualize data and translate simple ML results into actionable business intelligence.
• Provide basic client support for data engineering and ML workflows, escalating complex issues to senior team members.
• Participate in performance reviews of data pipelines and architectures under mentorship, suggesting improvements within defined scope.

【Requirements】

• Foundational understanding of data engineering principles, with basic proficiency in SQL, Python, or R.
• Basic knowledge of machine learning concepts (e.g., supervised/unsupervised learning, model evaluation) and frameworks like scikit-learn or TensorFlow.
• Enthusiasm for learning cloud technologies (AWS, Azure, GCP) and their applications in data infrastructure.
• Familiarity with BI tools (e.g., QuickSight, Tableau, Power BI) for basic data visualization tasks.
• Willingness to work under mentorship to develop expertise in ML model deployment and cloud-native services (e.g., AWS SageMaker, Azure ML).
• Exposure to AWS services (e.g., AWS Glue, Redshift) or Snowflake is a plus but not required; training will be provided.
• Strong problem-solving aptitude and openness to feedback, with a focus on skill development in both data engineering and ML.

【How to Apply】

Interested parties, please click APPLY NOW or send your resume with an expected salary and available date to Katie Ma by e-mail: katie.ma@ecloudvalley.com