全职 Data Engineer 工作, 薪水, Keyrus 公司招聘中 - Ricebowl

About the Role

We are seeking an experienced Data Engineer to join our growing data team. You will be responsible for designing, building, and maintaining scalable and reliable data pipelines and infrastructure to support analytics, machine learning, and business intelligence. The ideal candidate is passionate about data systems, thrives in a collaborative environment, and is eager to solve complex data challenges.

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Key Responsibilities

• Design, develop, and maintain robust, scalable ETL/ELT pipelines for batch and real-time data processing.

• Collaborate with data scientists, analysts, and business teams to understand data requirements and deliver structured, high-quality datasets.

• Build and optimize data warehouses, data lakes, and other data storage solutions to ensure data availability, consistency, and performance.

• Implement data quality frameworks, monitoring, and alerting systems to ensure data integrity and reliability.

• Work closely with engineering teams to deploy, manage, and troubleshoot data systems in production environments.

• Continuously evaluate and adopt new technologies and tools to improve the data platform’s efficiency and scalability.

• Ensure compliance with data governance, security policies, and regulatory requirements.

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Requirements

Must-have:

• Bachelor’s or higher degree in Computer Science, Engineering, Data Science, or a relevant field.

• At least 3 years of hands-on experience as a Data Engineer or in a similar role.

• Strong proficiency in SQL and at least one programming language (Python, Scala, or Java preferred).

• Experience with big data technologies such as Apache Spark, Hadoop, Kafka, or similar.

• Hands-on experience with cloud data services (AWS, GCP, or Azure) – e.g., AWS Redshift, S3, Glue; GCP BigQuery; Azure Data Factory, etc.

• Knowledge of data warehousing concepts, dimensional modeling, and ETL/ELT tools (e.g., dbt, Airflow, Prefect).

• Excellent problem-solving skills, with the ability to work independently and collaboratively in a fast-paced environment.

Good to have:

• Experience with modern data lake architectures (Delta Lake, Apache Iceberg, Hudi).

• Familiarity with real-time/streaming data processing (Kafka Streams, Flink, etc.).

• Understanding of data governance, security, and compliance standards (e.g., GDPR, PDPA).

• Previous experience in fintech, e-commerce, or high-growth tech environments.