資料工程師, Data Engineer, Presentation Group

Role Description: We are seeking a motivated and detail-oriented Data Engineer to join our growing data team. In this role, you will be instrumental in building and maintaining our data infrastructure, ensuring the efficient and reliable data flow for analysis and reporting. You will collaborate closely with data scientists, analysts, and other engineers to develop and implement data pipelines, optimize data storage, and contribute to the overall data strategy. This is an excellent opportunity for an early-career to mid-level professional to gain hands-on experience in a dynamic and data-driven environment. Responsibilities: -Data Pipeline Development and Maintenance: -Design, develop, and maintain robust and scalable data pipelines using Python and Airflow. -Extract, transform, and load (ETL/ELT) data from various sources into our data warehouse. -Monitor and troubleshoot data pipeline issues, ensuring data integrity and reliability. -Data Storage and Management: -Assist in the design and implementation of efficient data storage solutions on AWS. -Optimize database performance and contribute to data governance practices. -Maintain data schemas, data dictionaries, and documentation. Cloud Infrastructure (AWS): -Utilize AWS services such as S3, EMR, Redshift, and EC2 for data storage and processing. -Participate in the deployment and management of cloud-based data infrastructure. -Monitor and optimize cloud resource usage for cost-effectiveness and performance. -Collaboration and Communication: -Work closely with data scientists, analysts, and engineers to understand data requirements. -Collaborate cross-functionally to deliver reliable data solutions for analytics and product needs. -Document processes and communicate progress clearly to stakeholders. Required Skills: Programming & Data Engineering: -Proficiency in Python, with strong command of data manipulation libraries such as Pandas and NumPy. -Solid understanding of Hadoop and PySpark, with experience building distributed data processing workflows. -Experience with Apache Airflow for orchestrating and managing data workflows. Cloud & Data Systems: -Familiarity with Amazon Web Services (AWS), especially S3, EMR, Redshift, and EC2. -Understanding of ETL processes, relational databases, and data warehousing concepts. -Experience managing large-scale datasets and optimizing performance in distributed environments. Soft Skills: -Strong problem-solving and analytical thinking. -Excellent communication and collaboration skills. -Ability to learn quickly and adapt to evolving technologies. -High attention to detail and a structured, process-oriented mindset. Preferred Qualifications (Nice to Have): -Bachelor's degree in Computer Science, Data Science, or a related technical field. -Hands-on experience with dbt for building and maintaining data transformation models. -Experience working on LLM (Large Language Model) or AI-related projects, such as model integration, fine-tuning, or deploying AI-powered features in production. -Familiarity with data modeling best practices and version control (e.g., Git). -Knowledge of data visualization tools such as Power BI or similar platforms.