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For one of our client, we are seeking an experienced Data Engineer to join our dynamic team. The ideal candidate will have a solid background in data engineering, with expertise in Python, ETL tools, Airflow, and Hadoop. You will be responsible for building, maintaining, and optimizing data pipelines that handle high-volume transactions exceeding 50 million per day.
Key Responsibilities
- Design, develop, and maintain scalable data pipelines and data models for large transaction systems.
- Utilize Python and ETL tools to extract, transform, and load data efficiently from various sources.
- Implement and manage workflows using Apache Airflow to automate data processing tasks.
- Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and ensure data quality and availability.
- Optimize data processing performance and reliability in a Hadoop environment.
- Monitor and troubleshoot data pipeline issues to ensure operational efficiency and reliability.
- Document processes, data flow, and architecture for future reference and compliance.
- Stay current with industry trends and emerging technologies in data engineering.
Requirements
- 8+ years of experience in data engineering or a similar role.
- Strong proficiency in Python for data processing and manipulation.
- Hands-on experience with ETL tools (e.g., Talend, Informatica, Apache NiFi).
- In-depth knowledge of Apache Airflow for workflow management.
- Experience with big data technologies such as Hadoop and its ecosystem (e.g., HDFS, Hive, Spark).
- Proven experience in building and maintaining big transaction systems (handling over 50 million transactions per day).
- Familiarity with cloud platforms (e.g., AWS, Azure, GCP) is a plus.
- Excellent analytical and problem-solving skills.
- Strong communication skills and the ability to work collaboratively in a team environment.
Benefits:
Job ID: 142497071